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Decision-making processes and decision support systems (DSS) have been improved by a variety of methods originated from several scientific fields, such as information science and artificial intelligence (AI). Situated visualization (SV) allows presenting visual data representations in context and may support better DSS. Its main characteristic is to display data representations near the data referent. As augmented reality (AR) is becoming more mature, affordable, and widespread, using it as a tool for SV becomes viable in several situations. Moreover, it may provide a positive contribution to more effective and efficient decision-making, as the users have contextual, relevant, and appropriate information that fosters more informed choices. As new challenges and opportunities arise, it is important to understand the relevance of intertwining these fields. Based on literature analysis, this paper introduces the main concepts involved, and, through practical examples, addresses and discusses current areas of application, benefits, challenges, and opportunities of using SV through AR to visualize data in context to support better decision-making processes. In the end, a set of guidelines for the design and implementation of DSS based on situated augmented reality are proposed.

The traditional method for learning the multiplication tables is a repetitive and boring task. Teachers try to find new methods to motivate children in this tedious duty, and one of the lines to consider is to integrate en- tertainment into educational processes. This work presents a new multimedia interaction approach in order to allow children to practice these math opera- tions and have fun. The learning process has been gamified by means of two mini-games designed for mobile platforms, based on meromictic or repetitive learning. The genre of these mini-games have been selected according to chil- dren preferences: one turn-based fighting and other throwing-objects game. A series of proposed multiplications have to be solved during the play to per- form the player actions. Moreover, in order to support learning engagement, both have been visualized through Augmented Reality, combining real and virtual reality. This paper discusses the good results of mixing entertainment with some learning tasks, due to the engagement of the children to the mobile based games. A pilot study has been performed in order to evaluate the learn- ing effectiveness and usability of the proposal. Results support that playing the video games makes this tedious multiplication practice more enjoyable and attractive for children so they improve their math skills.

Computational fluid dynamics (CFD) simulations can provide meaningful technical content in engineering education, broad engineering and business. However, computationally demanding data production and complex data processing environments of CFD simulations turn them into esoteric tools for potential non-expert users. This consequently limits applications and communications of CFD simulations and results. Augmented and virtual reality (AR/VR) technologies are opening new gates for visualization and interaction techniques. Despite the many recent attempts, the literature lacks an inclusive system development procedure for CFD simulations with AR/VR. The present study proposes a component-oriented system architecture to generate dedicated workflows for any kind of AR/VR environment supported by CFD simulations. The study further explores the potential of data processing options throughout the preparation of the simulation dataset with AR/VR. An automated data coupling strategy is additionally introduced to ease multiplatform integration. We provide an integration strategy with simple, easy-to-implement, end-to-end, automated and free-to-use utilities that the practitioners can readily pursue.

The awareness of emerging trends is essential for strategic decision making because technological trends can affect a firm’s competitiveness and market position. The rise of artificial intelligence methods allows gathering new insights and may support these decision-making processes. However, it is essential to keep the human in the loop of these complex analytical tasks, which, often lack an appropriate interaction design. Including special interactive designs for technology and innovation management is therefore essential for successfully analyzing emerging trends and using this information for strategic decision making. A combination of information visualization, trend mining and interaction design can support human users to explore, detect, and identify such trends. This paper enhances and extends a previously published first approach for integrating, enriching, mining, analyzing, identifying, and visualizing emerging trends for technology and innovation management. We introduce a novel interaction design by investigating the main ideas from technology and innovation management and enable a more appropriate interaction approach for technology foresight and innovation detection.

Among the existing platforms, the mobile platform provides most of the augmented reality experiences for users. Augmented reality solutions have been applied in several contexts due to technological advances in this area. However, many of these advances are still out of reach of more massive access by regular users due to access limitations or the cost of these new technologies. After conducting a literature review considering the application of data visualization in augmented reality environments, we have identified an evolution of equipment used in this context with a decrease of low-cost proposals. Hence, the works related to these two areas showed high use of technologies not yet accessible to the vast majority of users. Thus, we propose a low-cost augmented reality application that can be used on mobile devices for data visualization. We developed a hybrid proposal of an augmented reality prototype to interacting with cards through the mobile device to support the process of creating data visualization. The tangible cards have a design that helps the user in the visualization creation process, indicating each card’s role in the interaction process. The proposed application supports a multi-user environment, allowing multiple users to interact simultaneously with data visualizations in the AR environment. The visualizations are generated on a dedicated server for this function, providing a set of seven different types of visualization. To validate the developed prototype we performed two tests, the first being a stress assessment on the server that generates data visualizations to analyze the proposed application’s scalability. The second was a remote usability test with twelve participants, to evaluate the interaction and design of the cards, and the viability of this solution for augmented reality applications.

We present Movie Emotion Map - a novel system that enables to view and browse through a large collection of movies according to the movies’ emotional characteristics. The system enables to view both the high-level structure of the movies emotional space and the low-level details of a single movie. We create an eight-dimensional emotional signature for each movie based on Plutchik’s theory of emotions, according to its reviews obtained from IMDb. We projected glyphs representing emotional signatures of the movies on a 2D plane using dimension reduction, thus, providing a topology of emotions for easy browsing and exploring. Results from a qualitative evaluation with 18 participants indicate that users could easily browse through movies according to the visualized landscape and that the tool enabled them to search, filter and find movies based on their emotional characteristics.

In the last few years, the integration of researches in Computer Science and medical fields has made available to the scientific community an enormous amount of data, stored in databases. In this paper, we analyze the data available in the Parkinson’s Progression Markers Initiative (PPMI), a comprehensive observational, multi-center study designed to identify progression biomarkers important for better treatments for Parkinson’s disease. The data of PPMI participants are collected through a comprehensive battery of tests and assessments including Magnetic Resonance Imaging and DATscan imaging, collection of blood, cerebral spinal fluid, and urine samples, as well as cognitive and motor evaluations. To this aim, we propose a technique to identify a correlation between the biomedical data in the PPMI dataset for verifying the consistency of medical reports formulated during the visits and allow to correctly categorize the various patients. To correlate the information of each patient’s medical report, Information Retrieval and Machine Learning techniques have been adopted, including the Latent Semantic Analysis, Text2Vec and Doc2Vec techniques. Then, patients are grouped and classified into affected or not by using clustering algorithms according to the similarity of medical reports. Finally, we have adopted a visualization system based on the D3 framework to visualize correlations among medical reports with an interactive chart, and to support the doctor in analyzing the chronological sequence of visits in order to diagnose Parkinson’s disease early.

To address the problem of feature points missing and surface holes after 3D reconstruction. A method of filling holes after extracting feature points of point cloud data is proposed. In this paper, the method of extracting feature points by multi-discriminant parameters is used to simplify the point cloud. The original shape features are retained while the data are simplified. Then, the initial triangulation of the point cloud is carried out. The resulting triangular mesh is least squared to get a relatively normal mesh, and finally the curvature of the surface is adjusted and optimized. The experimental results show that the simplification rate corresponding to improving the efficiency and retaining the original features is different for the point cloud data of different magnitude. The simplification rate of tens of thousands point cloud data is 70-80%, and that of hundreds of thousands of point cloud data is 40%. It also shows that the combination of feature point extraction and hole repair not only improves the efficiency of the repair process, but also retains the original features of the data.

Data visualization in high-dimensional space is a significant problem in machine learning. In many data sets, the data apparently lie on a high dimensional ambient space due to redundant features, while the intrinsic dimension is very low. This work proposes an analytical approach to use Feature Based Ricci Flow Embedding (FBRFE) as a nonlinear dimensionality reduction technique. For visualization purposes, we have considered nonlinear data with an intrinsic dimension of 2 D but lie on an ambient space 3 D and reduced the dimensionality accordingly. FBRFE uses conformal mapping that preserves the angle between the points in the higher dimensional manifold. At first, a surface triangulation mesh is formed using all the data points, and then circle packing is done in order to compute the respective angles between the data points. Then, conformal mapping is performed through the surface Ricci flow algorithm. After that, the 3 D surface triangulation mesh is flattened into 2 D using a seed face flattening algorithm to reduce the dimensionality of the data. Comparison results show that FBRFE visualizes the data in a lower dimension with a much better mean correlation up to 120.17 % and less overlapping than the existing conventional algorithms.

This paper presents an approach to the production of web-based interactive fiction, which is grounded in the requirements posed by an expert focus group, and which integrates a domain-specific language (DSL) for interactive fiction (HEXIFE) and an authoring tool for this DSL (IFDBMaker). HEXIFE is an extension of HMTL5 that includes markup specifically devoted to different aspects of interactive fiction, such as hyperlinking, choice points, personalization, stretchtext, annotations, conditional content, and gamification. This DSL, which can be easily extended with new interactive fiction behaviors, is supported by a runtime environment based on conventional web technologies (HTML5, CSS3, JavaScript, Web Components, PHP, and MySQL). IFDBMaker, in turn, piggybacks in a widely used web-based HTML editing framework (TinyMCE) to allow the creation of interactive HEXIFE fiction through a user-friendly approach. A postmortem evaluation shows how: (i) the approach makes the feasibility of supporting interactive fiction on conventional web technologies apparent; and (ii) the approach is a feasible one to actively involve writers in the final production of interactive fiction that are distributed and played through the web.