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Users frequently interact with software systems through data entry forms. However, form filling is time-consuming and error-prone. Although several techniques have been proposed to auto-complete or pre-fill fields in the forms, they provide limited support to help users fill categorical fields, i.e., fields that require users to choose the right value among a large set of options. In this paper, we propose LAFF, a learning-based automated approach for filling categorical fields in data entry forms. LAFF first builds Bayesian Network models by learning field dependencies from a set of historical input instances, representing the values of the fields that have been filled in the past. To improve its learning ability, LAFF uses local modeling to effectively mine the local dependencies of fields in a cluster of input instances. During the form filling phase, LAFF uses such models to predict possible values of a target field, based on the values in the already-filled fields of the form and their dependencies; the predicted values (endorsed based on field dependencies and prediction confidence) are then provided to the end-user as a list of suggestions. We evaluated LAFF by assessing its effectiveness and efficiency in form filling on two datasets, one of them proprietary from the banking domain. Experimental results show that LAFF is able to provide accurate suggestions with a Mean Reciprocal Rank value above 0.73. Furthermore, LAFF is efficient, requiring at most 317 ms per suggestion., Comment: Accepted for publication by ACM Transactions on Software Engineering and Methodology

Inceptor is a tool designed for non-expert users to develop social VR scenarios that includes virtual humans. The tool uses a text based interface and natural language processing models as input, and generates complete 3D/VR Unity scenarios as output. The tool is currently based on the Rocketbox asset library. We release the tool as an open source project in order to empower the extended reality research community.

Funding Information: This work was funded by the Department of Communications and Networking (Comnet), the Finnish Center for Artificial Intelligence (FCAI), Academy of Finland projects ‘Human Automata’ and ‘BAD’, HumaneAI Net (H2020 ICT 48 Network of Centers of Excellence), and Huawei Technologies. Authors’ addresses: L. Brückner and A. Oulasvirta, User Interfaces Research Group, Department of Communications and Networking, Konemiehentie 2, 13000 Aalto University, Finland; emails: paper@luksurious.me, antti.oulasvirta@aalto.fi; L. A. Leiva, Université du Luxembourg, Maison du Nombre, 6 Avenue de la Fonte, L-4364 Esch-sur-Alzette; email: luis.leiva@uni.lu. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2022 Copyright held by the owner/author(s). Publication rights licensed to ACM. 2160-6455/2022/02-ART6 $15.00 https://doi.org/10.1145/3490034 Publisher Copyright: © 2022 Copyright held by the owner/author(s). Publication rights licensed to ACM. | openaire: EC/H2020/952026/EU//HumanE-AI-Net A key objective in the design of graphical user interfaces (GUIs) is to ensure consistency across screens of the same product. However, designing a compliant layout is time-consuming and can distract designers from creative thinking. This paper studies layout recommendation methods that fulfill such consistency requirements using machine learning. Given a desired element type and size, the methods suggest element placements following real-world GUI design processes. Consistency requirements are given implicitly through previous layouts from which patterns are to be learned, comparable to existing screens of a software product. We adopt two recently proposed methods for this task, a Graph Neural Network (GNN) and a Transformer model, and compare them with a custom approach based on sequence alignment and nearest neighbor search (kNN). The methods were tested on handcrafted datasets with explicit layout patterns, as well as large-scale public datasets of diverse mobile design layouts. Our results show that our instance-based learning algorithm outperforms both neural network approaches. Ultimately, this work contributes to establishing smarter design tools for professional designers with explainable algorithms that increase their efficacy.

Industrial Augmented Reality (iAR) has demonstrated its advantages to communicate technical information in the fields of maintenance, assembly, and training. However, literature is scattered among different visual assets (i.e., AR visual user interface elements associated with a real scene). In this work, we present a systematic literature review of visual assets used in these industrial fields. We searched five databases, initially finding 1757 papers. Then, we selected 122 iAR papers from 1997 to 2019 and extracted 348 visual assets. We propose a classification for visual assets according to (i) what is displayed, (ii) how it conveys information (frame of reference, color coding, animation), and, (iii) why it is used. Our review shows that product models, text and auxiliary models are, in order, the most common, with each most often used to support operating, checking and locating tasks respectively. Other visual assets are scarcely used. Product and auxiliary models are commonly rendered world-fixed, color coding is not used as often as expected, while animations are limited to product and auxiliary model. This survey provides a snapshot of over 20 years of literature in iAR, useful to understand established practices to orientate in iAR interface design and to present future research directions.

Orientation and mobility apps for visually impaired people are well known to be effective in improving the quality of life for this target group. A mobile application that guides a visually impaired person step-by-step through a physical space is a valuable aid, but it does not provide an overview of a complex environment "at a glance," as a traditional hard-copy tactile map does. The aim of this study is to investigate whether a smartphone GPS map, enriched with haptic and audio hints, can facilitate cognitive mapping for visually impaired users. Encouraged by a preliminary study conducted in co-operation with two visually impaired volunteers, we designed and developed an Android prototype for exploration of an urban area. Our goal was to provide an affordable, portable and versatile solution to help users increase awareness of an environment through the positions of its landmarks and points of interest. Vibro-tactile and audio hints were linked to the coordinates on the map via the GeoJSON data format and were issued exploiting the text-to-speech and vibration features of the mobile device, as they were displayed through the operating system's APIs. Test sessions and interviews with visually impaired users produced encouraging results. Results, to be verified by more extensive testing, overall confirm the validity of our approach and are in line with results found in the literature.

This paper describes a study, which is currently underway, whose aim is to investigate how the haptic channel can be effectively exploited by visually impaired users in a mobile app for the preliminary exploration of an indoor environment, namely a shopping mall. Our goal was to use haptics to convey knowledge of how the points of interest (POIs) are distributed within the physical space, and at the same time provide information about the function of each POI, so that users can get a perception of how functional areas are distributed in the environment "at a glance". Shopping malls are typical indoor environments in which orientation aids are highly appreciated by customers, and many different functional areas persist. We identified seven typical categories of POIs which can be encountered in a mall, and then associated a different vibration pattern each. In order to validate our approach, we designed and developed a prototype for preliminary testing, based on the Android platform. The prototype was periodically debugged with the aid of two visually impaired experienced users, who gave us precious advice throughout the development process. We will describe how this app was conceived, the issues emerged during its development and the positive outcomes produced by a very early testing stage. Finally, we will show that the proposed approach is promising and is worthy of further investigation.

Various interventions have been suggested to aid in smoking cessation. However, little is known about the effects of message framing in narratives embedded in serious games. This study compares when an individual experiences unfortunate events from smoking (i.e., loss frame) versus fortunate results benefited from smoking cessation (i.e., gain frame) in a computer game through a model (i.e., virtual self-modeling) that looks like oneself or a stranger. An experiment (N = 64) using a 2 (Message framing: Gain vs. Loss) x 2 (Modeling: Self vs. Other) between-subjects design was conducted using an anti-smoking game. Results show that the gain frame induces stronger perceived susceptibility compared to the loss frame, and self-modeling is more effective than other-modeling. Results further demonstrate that the virtual misfortune experienced through one’s own face, compared to someone else’s face, is significantly more likely to increase one’s susceptibility to the negative consequences of smoking. The study also finds a significant mediating role of identification between framing and susceptibility. Overall, by demonstrating the effectiveness of the self-modeling and gain-framed messages in gameplay, the present investigation provides meaningful contributions to the use of technology for effective health communication. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF2019S1A5A2A03035424).

A variety of evaluation methods for user interfaces (UI) exist such as usability testing, cognitive walkthrough, and heuristic evaluation. However, UIs such as guidance systems at transit hubs must be evaluated in their intended application field to allow the effective and valid identification of usability flaws. However, what if evaluations are not feasible in real environments, or laboratorial conditions cannot be ensured? Based on adapted heuristics, in the present study, the method of heuristic evaluation is combined with immersive Virtual Reality (VR) for the identification of usability flaws of dynamic guidance systems (DGS) at transit hubs. The study involved usability evaluations of nine DGS concepts using the newly proposed method. The results show that compared to computer-based heuristic evaluations, the use of immersive VR led to the identification of an increased amount of “severe” usability flaws as well as overall usability flaws. Within a qualitative assessment, immersive VR is validated as a suitable tool for conducting heuristic evaluations involving significant advantages such as the creation of realistic experiences in laboratorial conditions. Future work seeks to further prove the suitability of using immersive VR for heuristic evaluations and compare the proposed method to other evaluative methods.

The 'Virtual Touch Toolkit' is the exergame bundle of a newly developed smartphone application for mental health. The primary aim of the exercises is to promote self-discovery by focusing on social, affective touch. The necessity of acknowledging the undervalued properties of affective touch in this day and age is more important than ever as a global pandemic is provoking societal changes that are predicted to be detrimental to our mutual need for affective touch. The toolkit comprises multiple features and sets of exercises, which are designed to stimulate the user's oxytocinergic and reward systems while offering educational insights on affective touch.

In this registration, we describe a planned study that aims to investigate the effects of time constraints and SERP interface on web search. The registration contains research questions, hypotheses, method, materials, procedure, and statistical analyses.

The visual system exploits multiple signals, including monocular and binocular cues, to determine the motion of objects through depth. In the laboratory, sensitivity to different three-dimensional (3D) motion cues varies across observers and is often weak for binocular cues. However, laboratory assessments may reflect factors beyond inherent perceptual sensitivity. For example, the appearance of weak binocular sensitivity may relate to extensive prior experience with two-dimensional (2D) displays in which binocular cues are not informative. Here we evaluated the impact of experience on motion-in-depth (MID) sensitivity in a virtual reality (VR) environment. We tested a large cohort of observers who reported having no prior VR experience and found that binocular cue sensitivity was substantially weaker than monocular cue sensitivity. As expected, sensitivity was greater when monocular and binocular cues were presented together than in isolation. Surprisingly, the addition of motion parallax signals appeared to cause observers to rely almost exclusively on monocular cues. As observers gained experience in the VR task, sensitivity to monocular and binocular cues increased. Notably, most observers were unable to distinguish the direction of MID based on binocular cues above chance level when tested early in the experiment, whereas most showed statistically significant sensitivity to binocular cues when tested late in the experiment. This result suggests that observers may discount binocular cues when they are first encountered in a VR environment. Laboratory assessments may thus underestimate the sensitivity of inexperienced observers to MID, especially for binocular cues.

Background This research reports on a pilot study that examined the usability of a reminiscence app called ‘InspireD’ using eye tracking technology. The InspireD app is a bespoke digital intervention aimed at supporting personalized reminiscence for people living with dementia and their carers. The app was developed and refined in two co‐creation workshops and subsequently tested in a third workshop using eye tracking technology. Intervention Eye tracking was used to gain insight into the user's cognition since our previous work showed that the think‐aloud protocol can add to cognitive burden for people living with dementia while also making the test more unnatural. Results Results showed that there were no barriers to using a wearable eye tracker in this setting and participants were able to use the reminiscence app freely. However, some tasks required prompts from the observer when difficulties arose. While prompts are not normally used in usability testing (as some argue the prompting defeats the purpose of testing), we used ‘prompt frequency’ as a proxy for measuring the intuitiveness of the task. There was a correlation between task completion rates and prompt frequency. Results also showed that people living with dementia had fewer gaze fixations when compared to their carers. Carers had greater fixation and saccadic frequencies when compared to people living with dementia. This perhaps indicates that people living with dementia take more time to scan and consume information on an app. A number of identified usability issues are also discussed in the paper. Patient or Public Contribution The study presents findings from three workshops which looked at user needs analysis, feedback and an eye tracking usability test combined involving 14 participants, 9 of whom were people living with dementia and the remaining 5 were carers.

The objective of this article was to establish the first contextual approaches for the development of a framework focused on the design of automotive infotainment systems. Therefore, a method was developed to identify a group of characteristics of the infotainment system interfaces that ensure a good user experience by the user, according to previous studies. Besides, the establishment of usability is proposed as a basis for the development of the tool.

Software engineers routinely use sketches (informal, ad-hoc drawings) to visualize and communicate complex ideas for colleagues or themselves. We hypothesize that sketching could also be used as a novel interaction modality in integrated software development environments (IDEs), allowing developers to express desired source code manipulations by sketching right on top of the IDE, rather than remembering keyboard shortcuts or using a mouse to navigate menus and dialogs. For an initial assessment of the viability of this idea, we conducted an elicitation study that prompted software developers to express a number of common IDE commands through sketches. For many of our task prompts, we observed considerable agreement in how developers would express the respective commands through sketches, suggesting that further research on a more formal sketch-based visual command language for IDEs would be worthwhile., Icelandic Research Fund (grant no. 196228), Post-print

International audience; The area of Engineering Interactive Computing Systems (EICS) is defined as the intersection between Software Engineering (SE) and Human-Computer Interaction (HCI). In this paper, we provide an overview of what EICS is and how it is positioned with respect to other venues in HCI, such as CHI, UIST, and IUI, highlighting its legacy and paying homage to past scientific events from which EICS emerged. We also take this opportunity to deliver a comparative analysis of the past, present, and perhaps future research and development questions raised in EICS by analyzing the EICS papers published from its first edition to this one, based on global and chronological word clouds, phrase nets, and topic modelling.

Recent advances in wearable sensor technology and smartphones enable simple and affordable collection of personal analytics. This paper reflects on the lessons learned in the SWELL project that addressed the design of user-centered ICT applications for self-management of vitality in the domain of knowledge workers. These workers often have a sedentary lifestyle and are susceptible to mental health effects due to a high workload. We present the sense–reason–act framework that is the basis of the SWELL approach and we provide an overview of the individual studies carried out in SWELL. In this paper, we revisit our work on reasoning: interpreting raw heterogeneous sensor data, and acting: providing personalized feedback to support behavioural change. We conclude that simple affordable sensors can be used to classify user behaviour and heath status in a physically non-intrusive way. The interpreted data can be used to inform personalized feedback strategies. Further longitudinal studies can now be initiated to assess the effectiveness of m-Health interventions using the SWELL methods.

We present the "ProofWidgets" framework for implementing general user interfaces (UIs) within an interactive theorem prover. The framework uses web technology and functional reactive programming, as well as metaprogramming features of advanced interactive theorem proving (ITP) systems to allow users to create arbitrary interactive UIs for representing the goal state. Users of the framework can create GUIs declaratively within the ITP’s metaprogramming language, without having to develop in multiple languages and without coordinated changes across multiple projects, which improves development time for new designs of UI. The ProofWidgets framework also allows UIs to make use of the full context of the theorem prover and the specialised libraries that ITPs offer, such as methods for dealing with expressions and tactics. The framework includes an extensible structured pretty-printing engine that enables advanced interaction with expressions such as interactive term rewriting. We exemplify the framework with an implementation for the https://leanprover-community.github.io. The framework is already in use by hundreds of contributors to the Lean mathematical library., LIPIcs, Vol. 193, 12th International Conference on Interactive Theorem Proving (ITP 2021), pages 4:1-4:16

International audience; We explore the features of a user interface where formal proofs can be built through gestural actions. In particular, we show how proof construction steps can be associated to drag-and-drop actions. We argue that this can provide quick and intuitive proof construction steps. This work builds on theoretical tools coming from deep inference. It also resumes and integrates some ideas of the former proof-by-pointing project.

Measurements of the depth of the seabed vary widely in both horizontal and vertical accuracy. To convey this information to mariners, Zones of Confidence (ZOC) are defined for charts. A mosaic of ZOCs can be represented as a chart overlay. This study evaluates two novel designs for textures to represent ZOCs. Both use textures with countable elements to represent different ZOC levels. One uses a texture made of lines where the number of lines in a texture cell represents the confidence level; the other uses dot clusters where the number of dots similarly represents the ZOC level. In the study, these were compared with three alternatives that used color to respond and accuracy as dependent variables. The dot clusters design yielded the fastest responses overall. A method using levels of color transparency proved to be the slowest and least accurate., Evaluation and Representation, Colin Ware and Christos Kastrisios

16 Pàg., This work has been partially funded by the European Commission through Cross-Forest (2017-EU-IA-0140) and Spanish Ministry of Science and Innovation through REFORM (PCIN-2017-027, ERANET SUMFOREST) projects. The authors would like to thank the reviewers for their constructive and insightful comments that helped to improve this paper

Recent technological advances in Machine Learning and Artificial Intelligence have led to the proliferation of AI-powered decision support systems. This partially explains the HCI research community’s increased interest in investigating how to design systems that will optimise Human-AI collaboration. However, most studies predominately focus on the work environment in which domain experts interact with AI systems to solve relatively well-defined tasks. In this paper, we explore Human AI collaboration involving non-domain experts in the everyday task of waste sorting for recycling. We conducted a study in which 35 participants completed a waste sorting task using Waste Wizard, an AI-infused prototype that we developed. We present the results of our qualitative analysis based on follow-up interviews aiming to understand how our participants perceived the role of the AI system during their collaboration. Our results show four distinct roles (Mirror, Assistant, Guide, and Oracle) that our participants ascribed to the AI system.

The DesignSafe [1] portal is a web-based application created to facilitate researchers in the natural hazards community, providing data storage, computational resources, and publication pipelines to its users. With partners such as the RAPID response field reconnaissance teams who collect data immediately after a disaster event, the geospatial component of the data is essential information needed in subsequent analysis. Storing, searching, and visualizing this geospatial information has subsequently become a need for the DesignSafe and natural hazards community. A typical field reconnaissance mission can generate many gigabytes of geotagged images, videos and point cloud datasets. To integrate these data with the DesignSafe platform, we have developed a new set of RESTful APIs and a single page application to store, query and visualize these datasets. As one of the requirements for these tools is tight integration with the existing DesignSafe platform, which is built using Tapis [2] APIs, we have implemented the GeoAPI as a separate microservice in the Tapis v2 platform. This design allows us to easily utilize the existing data storage and user management tools built into DesignSafe. Users can access their existing data that is shared with their colleagues and already stored on the DesignSafe platform. Similarly, by utilizing the authentication services in Tapis, users can access these services with a single account. The backend has been developed using Python and the Flask framework. Application data is stored in a Postgres database with the PostGIS extension providing geospatial indexing. We have leveraged open-source libraries in the application such as GDAL, PDAL, Laspy, GeoPandas, and Shapely. Reconnaissance teams often use Lidar to collect point cloud data of structures damaged during a natural hazard event. These datasets alone can grow to many hundreds of GB and require additional processing. We use Celery to asynchronously process these data with Potree [3] to visualize them in the browser. Static assets such as images and videos are saved into a Ceph filesystem and are served directly by a Nginx proxy for performance. Maps can be automatically generated from data already in DesignSafe and asynchronously updated when new data is added to the storage system. The application is deployed into a Kubernetes cluster at TACC. A general architecture diagram is shown in figure 1. To visualize these datasets, we have created Hazmapper 2.0, a single page web application. This application was written in TypeScript using the Angular framework and Leaflet libraries. Additionally, we use an auto generated client library Ng-Tapis [4] to interact with the Tapis APIs. By doing so, we can utilize the API directly from the browser without the need for a separate backend application. External map tiles can be imported through a searchable interface using QuickMapServices (QMS) APIs [5]. The decoupled backend architecture allows us to have multiple user interfaces that are specialized for different end-user needs. One such example is the Taggit [6] application from Designsafe researchers. Separate from Hazmapper, this application allows for tagging and classification of georeferenced images.

International audience; Bau and Mackay's OctoPocus dynamic guide helps novices learn, execute, and remember 2D surface gestures. We adapt OctoPocus to 3D mid-air gestures in Virtual Reality (VR) using an optimization-based recognizer, and by introducing an optional exploration mode to help visualize the spatial complexity of guides in a 3D gesture set. A replication of the original experiment protocol is used to compare OctoPocus in VR with a VR implementation of a crib-sheet. Results show that despite requiring 0.9s more reaction time than crib-sheet, OctoPocus enables participants to execute gestures 1.8s faster with 13.8% more accuracy during training, while remembering a comparable number of gestures. Subjective ratings support these results, 75% of participants found OctoPocus easier to learn and 83% found it more accurate. We contribute an implementation and empirical evidence demonstrating that an adaptation of the OctoPocus guide to VR is feasible and beneficial.

Summarization: Glanceable interfaces are Augmented Reality (AR) User Interfaces (UIs) for information retrieval ”at a glance” relying on eye gaze for implicit input. While they provide rapid information retrieval, they often occlude a large part of the real-world. This is compounded as the amount of virtual information increases. Interacting with complex glanceable interfaces often results in unintentional eye gaze interaction and selections due to the Midas Touch problem. In this work, we present Holo-box, an innovative AR UI design that combines 2D compact glanceable interfaces with 3D virtual ”Holo-boxes”. We can utilize the glanceable 2D interface to provide compact information at a glance while using Holo-box for explicit input such as hand tracking activated when necessary, surpassing the Midas Touch problem and resulting in Level-of-Detail(LOD) for AR glanceable UIs. We test our proposed system inside a real-world machine shop to provide on-demand virtual information while minimizing unintentional real-world occlusion. Παρουσιάστηκε στο: Special Interest Group on Computer Graphics and Interactive Techniques Conference Posters

An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed methods being continuously introduced in the scientific literature. Despite the growing interest in entropic time series and image analysis, there is a shortage of validated, open-source software tools that enable researchers to apply these methods. To date, packages for performing entropy analysis are often run using graphical user interfaces, lack the necessary supporting documentation, or do not include functions for more advanced entropy methods, such as cross-entropy, multiscale cross-entropy or bidimensional entropy. In light of this, this paper introduces EntropyHub, an open-source toolkit for performing entropic time series analysis in MATLAB, Python and Julia. EntropyHub (version 0.1) provides an extensive range of more than forty functions for estimating cross-, multiscale, multiscale cross-, and bidimensional entropy, each including a number of keyword arguments that allows the user to specify multiple parameters in the entropy calculation. Instructions for installation, descriptions of function syntax, and examples of use are fully detailed in the supporting documentation, available on the EntropyHub website– www.EntropyHub.xyz. Compatible with Windows, Mac and Linux operating systems, EntropyHub is hosted on GitHub, as well as the native package repository for MATLAB, Python and Julia, respectively. The goal of EntropyHub is to integrate the many established entropy methods into one complete resource, providing tools that make advanced entropic time series analysis straightforward and reproducible.

The graphical and interactive design of a consent form helps individuals to keep control and pay attention to the information that they are disclosing. In the context of mobile apps we propose and test alternative interaction design solutions for selecting personal information on permission dialogues, namely using checkboxes, a drag-and-drop selection, and a swiping action. We test each proposed design and compare the results in terms of their usability and effectiveness in helping users to be more attentive and aware of their data flow, in other words, to provide their informed consent. This study demonstrates that checkboxes while speedy do not engage the user as much as drag-and-drop or swiping. User satisfaction is positively impacted by these newer ways of giving consent.

Business platform models frequently require continuous adaptation and agility to allow new experiences to be created and delivered to customers. To understand user behavior in online systems, researchers have taken advantage of a combination of traditional and recently developed analysis techniques. Earlier studies have shown that user behavior monitoring data, as obtained by mouse tracking, can be utilized to improve user experience (UX). Many mouse-tracking solutions exist; however, the vast majority is proprietary, and open-source packages do not provide the resources and data needed to support UX research. Thus, this paper presents: 1) the development of an interaction monitoring application titled Artificial Intelligence and Mouse Tracking-based User eXperience Tool (AIMT-UXT); 2) the validation of the tool in a case study conducted on the Website of the Brazilian Federal Revenue Service (BFR); 3) the definition of a new relationship pattern of variables that determine user behavior; 4) the construction of a fuzzy inference system for measuring user performance using the defined variables and the data captured in the case study; and 5) the application of a clustering algorithm to complement the analysis. A comparison of the results of the applied quantitative methodologies indicates that the developed framework was able to infer UX scores similar to those reported by users in questionnaires.

We present an enhanced version of the input device evaluation application (IDEA) system as an objective method for evaluating upper limb motor skills performance. By introducing three new metrics for mouse cursor trajectory analysis, along with the application of the two-dimensional (2D) experiment in the case of multiple sclerosis (MS), we examine the sensitivity of the IDEA system for differentiating patients with early-stage MS and healthy participants. The IDEA system calculates multiple kinematic metrics for point-and-click tasks: movement time, index of difficulty, effective target width, effective index of difficulty, throughput, missed clicks, target re-entry, task axis crossing, movement direction change, orthogonal direction change, movement variability, movement error, movement offset, mean velocity, velocity peaks, and maximum/mean velocity ratio. The results reveal that the IDEA system sensitivity has been improved in comparison with previous studies, which is high enough to detect the presence of early-stage MS with a 70.9% success rate in the 2D experiment.

Modern production systems have become highly complex, given technological progress and competitive market needs. However, the role of human operators keeps being fundamental since they are in charge of supervising machines and take proper action in the presence of alarms and faults. As a consequence, the design of effective and easy to use human-machine interfaces (HMIs) is a key component of overall production efficiency. In this paper we provide an extensive overview of different methods to assess the usability of HMIs for industrial operators. In particular, the methods covered by the survey range from subjective assessment to objective quantitative analysis that takes into account user’s mental fatigue, user’s interaction strategies and production efficiency.

In this paper, we introduce the idea of the ‘visibility matrix’ for automated data entry form generation in low-code development platforms. We then focus on the problem of software development productivity in the area of automated software generation as the main factor of the Industry 4.0 concept in the area of business information. In our study, two different approaches to user interface development in a business process management low-code platform were evaluated. The first, the multi-form model, assumes that input forms are prepared separately for each user task in the business process being automated. The second approach, the single-form model, assumes that there is one global input form for every task in the business process. Since users have access to different data in different process tasks, it is necessary to prepare the visibility matrix to define which data are relevant to which tasks. The experiments presented in this paper help to answer the following question: which approach yields better results in terms of productivity, which is measured as costs and time required to prepare the application? Several dozen real business processes were analysed to examine the properties of their visibility matrix. Additionally, the real project team members were evaluated to determine their productivity. Then, the productivity parameters were calculated for real business processes and real project teams. The results show which approach is better suited for real-world business process development.

Within the Virtual Interiors project various Amsterdam houses are reconstructed in three dimensions based on historical research. One of the case studies is the house of 17th-century Amsterdam-born patrician Pieter de Graeff and his wife Jacoba Bicker. The interdisciplinary dataset resulting from this case study (detailed in Piccoli, 2021) is presented within an online 3D research environment, which also serves as a starting point for further exploration of historical data. In earlier work (Huurdeman & Piccoli, 2021), we described this as a three-step process model of knowledge creation, sharing and discovery: new insights emerge during the creation of the 3D reconstructions (1), these insights are shared via an online research environment (2) and users may discover new knowledge through interacting with the environment and additional Linked Data (3). This paper focuses on the third step, the integration of related Linked Data relevant for Humanities researchers in a 3D research environment. The paper summarizes the experiences of utilizing Linked Data within the Humanities as extensions of created datasets in novel analytical and experiential interfaces based on 3D reconstructions. We discuss opportunities and pitfalls, from the perspective of the data, including data availability and quality, and from the perspective of integrating this data into user interfaces allowing for knowledge discovery. Further, we demonstrate the current research environment prototype, which is fully functional and provides flexibility by allowing for visualizing different datasets and 3D models. In addition, we discuss the initial findings of a user study in which Humanities researchers directly explore these user interfaces, leading to further insights into their potential for knowledge discovery. View presentation (Google Slides).

Las plataformas digitales editoriales son complejos sistemas de comunicación académica que deben incorporar soluciones de arquitecturas de la información para diversos niveles de acceso a los contenidos. Entre tales niveles destacan el de la publicación como un todo, y el de cada artículo individual. Además, para potenciar las genuinas propiedades del mundo digital, estas plataformas deben ofrecer funciones de descubrimiento de la información, y no solamente de acceso. Las primeras pueden implementarse gracias a la hipertextualidad y, más en concreto, gracias a enlaces basados en semejanza semántica. En este trabajo presentamos una revisión de las diferentes soluciones aportadas en estos elementos por cinco plataformas digitales de gran significación. [en] Digital publishing platforms are complex academic communication systems that must incorporate information architecture solutions to enable content access at various levels, including the whole publication and each individual article. In addition, to truly harness the advantages offered by the digital world, such platforms must also offer information discovery functions as well as access to information. The former can be implemented by using hypertextuality and, more specifically, links based on semantic similarity. We present herein a review of the various solutions provided in these regards by five important digital platforms.

Orientadores: Maria Cecília Calani Baranauskas, Rodrigo Bonacin Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação Resumo: De acordo com W3C, o valor social da Web está no fato de que ela possibilita a comunicação, o comércio, e oportunidades de troca de conhecimento. Estes benefícios deveriam estar disponíveis para todas as pessoas, com o hardware e versão do software que utilizam, sua infra-estrutura de rede, linguagem nativa, cultura, localização geográfica, habilidade física e conhecimento. Estes aspectos estão relacionados tanto a questões sociais quanto tecnológicas. Considerando a diversidade de usuários e a complexidade de situações possíveis de uso da Web, buscam-se soluções para interfaces mais flexíveis, que possibilitem sua adaptação a diferentes contextos de uso. Este trabalho apresenta uma abordagem para solucionar o problema de como desenvolver interfaces de usuário flexíveis para sistemas Web, investigando como interfaces poderiam ser adaptadas a diferentes contextos de uso, considerando o conceito de normas da Semiótica Organizacional. Tal abordagem está representada em um framework, proposto neste trabalho, para apoiar designers e desenvolvedores na construção de interfaces flexíveis. Resultados obtidos na aplicação do framework em um sistema Web real, inserido no contexto da inclusão digital e acesso universal, são apresentados e discutidos nesta obra. Tais resultados são sugestivos da viabilidade da proposta e apontam para seu aprofundamento futuro Abstract: According to W3C, the social value of the Web is in the fact that it enables communications, business and knowledge sharing opportunities. These benefits should be available for every person regardless of the person's hardware, software, network infrastructure, native language, cultural aspects, geographical location, physical and mental abilities. These aspects are related both to social and technological issues. Considering the differences among users and the complexity of possible Web usage, solutions are sought for more flexible user interfaces that allow their adaptation to different use contexts. This work presents an approach to solve the problem of developing flexible user interfaces for Web systems, investigating how interfaces can be adapted to different use contexts considering the concept of norms from Organizational Semiotics. This approach is represented by a framework, proposed on this work, that may help designers and developers to build flexible Web interfaces that may be adapted according to each use context. Results gathered when the framework was applied in a real Web system related to the context of universal access and digital inclusion are presented and discussed. Such results are suggestive of the proposal's viability and point to further improvements in future research Mestrado Interação Humano-Computador Mestre em Ciência da Computação

ObjectiveSo-called “Visual Restitution Therapies” (VRT) claim to ameliorate visual field defects of neurological patients by repeated visual light stimulation, leading to training-related neuroplasticity and resulting in reconnection of lesioned neurons in early cortical areas. Because existing systems are stationary, uncomfortable and unreliable, we developed a training instrument based on virtual reality goggles. The goal of the “Salzburg Visual Field Trainer” (SVFT) is twofold: (1) The device facilitates the clinical evaluation of established neuropsychological rehabilitation approaches, such as VRT. (2) The device enables patients to independently perform VRT based (or other) neuropsychological training methodologies flexibly, comfortably and reliably.Methods and AnalysisThe SVFT was developed on the principles of VRT. Individual configuration of the SVFT is based on perimetric data of the respective patient’s visual field. To validate the utmost important procedure in neuropsychological rehabilitation methodologies - that is displaying stimuli precisely in desired locations in the user’s visual field - two steps were conducted in this proof-of-concept study: First, we assessed the individual “blind spots” location and extent of 40 healthy, normal sighted participants. This was done with the help of our recently developed and validated perimetric methodology “Eye Tracking Based Visual Field Analysis” (EFA). Second, depending on the individual characteristics of every participant’s blind spots, we displayed - with the help of the SVFT - 15 stimuli in the respective locations of every participants’ blind spots and 85 stimuli in the surrounding, fully intact visual area. The ratio between visible and non-visible stimuli, which reflects in the documented behavioral response (clicks on a remote control) of the 40 participants, provides insight into the accuracy of the SVFT to display training stimuli in areas desired by the investigator. As the blind spot is a naturally occurring, absolute scotoma in human vision, we utilized this blind area as an objective criterion and a “simulated” visual field defect to evaluate the (technical) methodology of SVFT.ResultsOutcomes indicate that the SVFT and its methodology is highly accurate in displaying training stimuli in desired areas of the user’s visual field with an accuracy of 99.0%. Data analysis further shows a sensitivity of .980, specificity of .992, positive predictive value of .955, negative predictive value of .996, hit rate of .990, random hit rate of .742 and RATZ-Index of .976. This translates to 14.7% correct non-reactions, 0.7% false non-reactions, 0.3% false reactions and 84.3% correct reactions to displayed test stimuli during the evaluation study with the SVFT. Reports from participants further indicate that the SVFT is comfortable to wear and intuitive to use.ConclusionsThe SVFT can help to investigate the true effects of VRT based methodologies (or other neuropsychological approaches) and the underlying mechanisms of training-related neuroplasticity in early regions of the visual cortex in neurological patients suffering from visual field defects.

During an Ebola virus disease (EVD) outbreak, calculating the exposure window of a confirmed case can assist field investigators in identifying the source of infection and establishing chains of transmission. However, field investigators often have difficulty calculating this window. We developed a bilingual (English/French), smartphone-based field application to assist field investigators in determining the exposure window of an EVD case. The calculator only requires the reported date of symptoms onset and the type of symptoms present at onset or the date of death. Prior to the release of this application, there was no similar electronic capability to enable consistent calculation of EVD exposure windows for field investigators. The Democratic Republic of the Congo Ministry of Health endorsed the application and incorporated it into trainings for field staff. Available for Apple and Android devices, the calculator continues to be downloaded even as the eastern DRC outbreak resolved. We rapidly developed and implemented a smartphone application to estimate the exposure window for EVD cases in an outbreak setting

Designing interaction for Augmented Reality assembly applications is a challenging task. Hand based interaction metaphors supported by modern AR Head Mounted Displays are not always intuitive and may cause fatigue with prolonged use. This problem can be addressed by considering context knowledge of the assembly task for which the AR application is developed. Integrating context knowledge in the interaction may not only help user to interact faster but also lead towards an optimum assembly. In this paper, we present an adaptable constraints- based interaction system that assists users in interacting with virtual components in AR assembly applications. We demonstrate our interaction system with a spacecraft design use case in which users virtually assemble the components of a spacecraft. It combines constraint-based interaction with a suggestion mechanism. The constraints are defined by a set of rules built into the application which enforce self-consistency by defining the inter-relationships of the components leading to an optimum configuration. Our interface provides users with the freedom to move the components around, but prevents movements that are not in accordance with the defined rules. In addition to the constraints, it also suggests the optimum location for a component in the spacecraft based upon an optimization criteria. In the end, we evaluate our suggestion system through a user study. Our results indicate that optimized suggestions are time efficient, easy to use and a preferred choice of the users.

In our poster we present the design of the study, which will be conducted in the Virtual Environment with the usage of psychophysiology (EDA, HR and pupil size) and eye-tracking. Although many papers implementing aforementioned methods have been carried out to date, we believe that these techniques are still not fully utilized. Therefore, the focus in our work is on the methodological steps we have taken and technical topography we created to provide proper ground for the measurement. Our aim was to increase the signal-to-noise ratio, achieve higher confounders control and obtain reliable results.

International audience; During crisis, different organizations are involved, each with their jargon and communication devices. Information about the situation is needed by all and it is vital to be able to share the data. To centralize that data, Common Operational Pictures are implemented, but they do not remove the risk of information overload. We propose to use virtual reality to create a virtual environment improving COP representations, thus improving situational awareness and collaborative decision making.

In this paper, we present a psychophysical study exploring how spatialized sound affects perceptual detection thresholds for rotation gains during exposure to virtual environments with varying degrees of visibility. The study was based on a 2×3 factorial design, crossing two types of audio (no audio and spatialized audio) and three degrees of visibility (low, medium, and high density fog). We found no notable effects of sound spatialization or visibility on detection thresholds. Although future studies are required to empirically confirm that vision dominates audition, these results provide quantitative evidence that visual rotation gains may be robust to auditory interference. Furthermore, they suggest that rotation gains may be useful even when the virtual environment offers very limited visibility.

MARTYR is a dinner performance that explores food and collective virtual reality and premiered on October 22nd 2020. In this paper, we present the evaluation of two prototypes used to explore how virtual reality can affect dining experiences and how food can be used as an ingredient in virtual narratives. The results indicate that virtual reality can be used to affect perceived taste. However, the effect varied considerably between participants. Moreover, the participants appeared to accept food as an element of a virtual story, but it is unclear to what extent taste affected their experience of the narrative.

In this paper we present a simulation and validation of the Ambisonic concert hall at the Royal Danish Academy of Music (RDAM), which was inaugurated on September 19th, 2019 in Copenhagen.Validation with experts showed that the simulated ambisonic room was perceived to match the acoustic- and spatial attributes of its real counterpart.

Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells’ activity over repeated traversals of an environment (Stability method); a combination of these parameters with the size of the place field (Combination method); and the spatial information held by the cells (Information method). The methods performed differently from each other on both model and real data. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. Ultimately, we recommend the Peak method be used in future studies to identify place cell populations, as this method is robust to moderate variations in place field within a session, and makes no inherent assumptions about the spatial information in place fields, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties., Author summary Place cells are hippocampal cells that have spatially constrained receptive fields, the place field. These cells have been widely studied in the context of navigation, more recently using virtual reality environments in combination with optical methods of recording neuronal activity. However, there is a lack of consensus regarding how to identify place cells in these data. In this study we tested the sensitivity and specificity of four methods of identifying place cells. By comparing these methods and quantifying the populations of place cells they identify, we aimed to increase our understanding of exactly the populations that are currently being studied under the name “place cells”. Although the appropriate method may depend on the experimental design, we generally recommend a single method going forward, which will increase consensus within the field about what should be included in a place cell population, and allow us to better compare results between studies.

Working with organs and extracted tissue blocks is an essential task in surgery and anatomy environments. To prepare specimens from human donors for analysis, wet-bench workers must dissect human tissue and collect metadata for downstream analysis, including information about the spatial origin of tissue. The Registration User Interface (RUI) was developed to allow stakeholders in the Human Biomolecular Atlas Program (HuBMAP) to register tissue blocks, i.e., to record the size, position, and orientation of human tissue data with regard to reference organs. In this paper, we compare three setups for registering one 3D tissue block object to another 3D reference organ (target) object. The first setup is a 2D Desktop implementation featuring a traditional screen, mouse, and keyboard interface. The remaining setups are both virtual reality (VR) versions of the RUI: VR Tabletop, where users sit at a physical desk which is replicated in virtual space; VR Standup, where users stand upright while performing their tasks. We then ran a user study for these three setups involving 42 human subjects completing 14 increasingly difficult and then 30 identical tasks in sequence and reporting position accuracy, rotation accuracy, completion time, and satisfaction. While VR Tabletop and VR Standup users are about three times as fast and about a third more accurate in terms of rotation than 2D Desktop users (for the sequence of 30 identical tasks), there are no significant differences between the three setups for position accuracy when normalized by the height of the virtual kidney across setups., 45 pages/9 figures in main text (incl. references); 6 pages with 2 tables in Supporting Information

Long non-coding RNAs (lncRNAs) are defined as transcripts of greater than 200 nucleotides that play a crucial role in various cellular processes such as the development, differentiation and gene regulation across all eukaryotes, including plant cells. Since the last decade, there has been a significant rise in our understanding of lncRNA molecular functions in plants, resulting in an exponential increase in lncRNA transcripts, while these went unannounced from the major Angiosperm plant species despite the availability of large-scale high throughput sequencing data in public repositories. We, therefore, developed a user-friendly, open-access web interface, AlnC (Angiosperm lncRNA Catalogue) for the exploration of lncRNAs in diverse Angiosperm plant species using recent 1000 plant (1KP) trancriptomes data. The current version of AlnC offers 10,855,598 annotated lncRNA transcripts across 682 Angiosperm plant species encompassing 809 tissues. To improve the user interface, we added features for browsing, searching, and downloading lncRNA data, interactive graphs, and an online BLAST service. Additionally, each lncRNA record is annotated with possible small open reading frames (sORFs) to facilitate the study of peptides encoded within lncRNAs. With this user-friendly interface, we anticipate that AlnC will provide a rich source of lncRNAs for small-and large-scale studies in a variety of flowering plants, as well as aid in the improvement of key characteristics in relevance to their economic importance. Database URL: http://www.nipgr.ac.in/AlnC

Movement of the visual environment presented through virtual reality (VR) has been shown to invoke postural adjustments measured by increased body sway. The effect of auditory information on body sway seems to be dependent on context with sounds such as white noise, tones, and music being used to amplify or suppress sway. This study aims to show that music manipulated to match VR motion further increases body sway. Twenty-eight subjects stood on a force plate and experienced combinations of 3 visual conditions (VR translation in the AP direction at 0.1 Hz, no translation, and eyes closed) and 4 music conditions (Mozart’s Jupiter Symphony modified to scale volume at 0.1 Hz and 0.25 Hz, unmodified music, and no music) Body sway was assessed by measuring center of pressure (COP) velocities and RMS. Cross-coherence between the body sway and the 0.1 Hz and 0.25 Hz stimuli was also determined. VR translations at 0.1 Hz matched with 0.1Hz shifts in music volume did not lead to more body sway than observed in the no music and unmodified music conditions. Researchers and clinicians may consider manipulating sound to enhance VR induced body sway, but findings from this study would not suggest using volume to do so.

Analysis of overlapping spatial data sets is a challenging problem with tension between clearly identifying individual surfaces and exploring significant overlaps/conflicts. One area where this problem occurs is when dealing multiple flood scenes that occur in an area of interest. In order to allow easier analysis of scenes with multiple overlapping data layers, we introduce a visualization system designed to aid in the analysis of such scenes. It allows the user to both see where different data sets agree, and categorize areas of disagreement based on participating surfaces in each area. The results are stable with regard to render order and GPU acceleration via OpenCL allows interaction with large datasets with preprocessing dynamically. This interactivity is further enhanced by data streaming which allows datasets too large to be loaded directly onto the GPU to be processed. After demonstrating our approach on a diverse set of ensemble datasets, we provide feedback from expert users., Workshop on Visualisation in Environmental Sciences (EnvirVis), Probabilistic and Uncertainty-based Techniques for Environmental Data Visualization, 1, 8, Donald W. Johnson and T. J. Jankun-Kelly, Categories and Subject Descriptors (according to ACM CCS): I.3.8 [Computer Graphics]: Applications-Visualization H.5.2 [Information Interfaces and Presentation]: User Interfaces-Graphical user interfaces

This work presents Air Quality Temporal Analyser (AQTA), an interactive system to support visual analyses of air quality data with time. This interactive AQTA allows the seamless integration of predictive models and detailed patterns analyses. While previous approaches lack predictive air quality options, this interface provides back-and-forth dialogue with the designed multiple Machine Learning (ML) models and comparisons for better visual predictive assessments. These models can be dynamically selected in real-time, and the user could visually compare the results in different time conditions for chosen parameters. Moreover, AQTA provides data selection, display, visualisation of past, present, future (prediction) and correlation structure among air parameters, highlighting the predictive models effectiveness. AQTA has been evaluated using Stuttgart (Germany) city air pollutants, i:e:, Particular Matter (PM) PM10, Nitrogen Oxide (NO), Nitrogen Dioxide (NO2), and Ozone (O3) and meteorological parameters like pressure, temperature, wind and humidity. The initial findings are presented that corroborate the city’'s COVID lockdown (year 2020) conditions and sudden changes in patterns, highlighting the improvements in the pollutants concentrations. AQTA, thus, successfully discovers temporal relationships among complex air quality data, interactively in different time frames, by harnessing the user's knowledge of factors influencing the past, present and future behavior, with the aid of ML models. Further, this study also reveals that the decrease in the concentration of one pollutant does not ensure that the surrounding air quality would improve as other factors are interrelated., Workshop on Visualisation in Environmental Sciences (EnvirVis), Interactive Digital and Virtual Visualization Techniques for Environmental Data Visualization, 43, 50, Shubhi Harbola, Steffen Koch, Thomas Ertl, and Volker Coors, Keywords: Time series, environmental visualisation, user interfaces, visual prediction, machine learning, meteorological data, city planning, visual analytics, air pollutants

The behavior of the brain depends to a large extend on its neural structure. Therefore, understanding this neural topology is a high-priority research line for neurobiologists. Due to complexity of the brain's neural structure, visual representations look tangled, and extracting knowledge from them is a difficult task. In this work, we propose the use of multimodal interfaces to enhance neurobiologists' understanding of neural data. Our system is based on four pillars: a stereo rendering module, a camera control system, a visual aid unit, and a haptically constrained navigation tool. We observe that haptically aided navigation helps neurobiologists analyze the brain's topology. Our system uses stylus-based haptic devices with two purposes: they provide a natural interface to deal with 3D data (controlling camera motion) and they constrain the user's motion. The system was built trying to keep user interactions as intuitive as possible., V Ibero-American Symposium in Computer Graphics, DatData Visualization, 43, 46, Laura Raya, Miguel A. Otaduy, and Marcos García, Categories and Subject Descriptors (according to ACM CCS): I.3.4 [Computer Graphics]: Graphics Utilities-Virtual device interfaces. I.3.8 [Computer Graphics]: Applications-. H.5.2 [Information Interfaces and presentation]: User Interfaces-Haptic

This book constitutes the refereed post-conference proceedings of the 8th International Conference on Digital Heritage, EuroMed 2020, held virtually in November 2020.The 37 revised project papers and 30 revised short papers presented were carefully reviewed and selected from 326 submissions. The papers are on topics such as digital data acquisition technologies in CH/2D and 3D data capture methodologies and data processing; remote sensing for archaeology and cultural heritage management and monitoring; interactive environments and applications; reproduction techniques and rapid prototyping in CH; e-Libraries and e-Archives in cultural heritage; virtual museum applications (e-Museums and e-Exhibitions); visualisation techniques (desktop, virtual and augmented reality); storytelling and authoring tools; tools for education; 2D and 3D GIS in cultural heritage; and on-site and remotely sensed data collection.

One of the significant limitations in human behaviour when receiving online information is our lack of visual cognitive abilities, the ability to pay greater attention in a short time. The question arises about how we handle online messages, which contain and send people with the same associated interests as ourselves, regarding social influences and individual beliefs. This study aims to provide some insight into misinformation sharing. The availability of enormous amounts of COVID-19 information makes the selectivity of messages likely limited by the distortion of perceptions in the communicating environment. It is also in line with the fact that human attention is essentially limited and depends on the conditions and tasks at hand. To understand this phenomenon, we proposed a Tuning Attention Model (TAM). The model proposes tuning and intervene in a user’s attention behaviour by incorporating an attention-based design when users decide to share COVID-19 misinformation. In pilot study results, we found that attention behaviour negatively correlated with misinformation sharing behaviour. The results justify that when attention behaviour increased, misinformation sharing behaviour will decrease. We suggest an attention-based design approached on social media application’s that could intervene in user attention and avoid selective exposure caused by the spread of COVID-19 misinformation. The study expected to produce continuous knowledge leading to non-coercive handling of sharing COVID-19 misinformation behaviour and laying the basis for overcoming misinformation issues.