An interactive 3-D application for pain management: Results from a pilot study in spinal cord injury rehabilitation

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ElevierResearch on pain following spinal cord injury (SCI) has revealed that patients not only experience several types of pain that could prove to be challenging to address, but also that each individual can interpret such pain in different subjective ways. In this paper we introduce a 3-D system for facilitating the efficient management of pain, and thus, supporting clinicians in overcoming the aforementioned challenges. This system was evaluated by a cohort of 15 SCI patients in a pilot study that took place between July and October 2010. Participants reported their experiences of using the 3-D system in an adapted version of the System Usability Scale (SUS) questionnaire. Statistically significant results were obtained with regards to the usability and efficiency of the 3-D system, with the majority of the patients finding it particularly useful to report their pain. Our findings suggest that the 3-D system can be an efficient tool in the efforts to better manage the pain experience of SCI patients

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Self-Organising Map Approach to Individual Profiles: Age, Sex and Culture in Internet Dating

A marked feature of recent developments in the networked society has been the growth in the number of people making use of Internet dating services. These services involve the accumulation of large amounts of personal information which individuals utilise to find others and potentially arrange offline meetings. The consequent data represent a challenge to conventional analysis, for example, the service that provided the data used in this paper had approximately 5,000 users all of whom completed an extensive questionnaire resulting in some 300 parameters. This creates an opportunity to apply innovative analytical techniques that may provide new sociological insights into complex data. In this paper we utilise the self-organising map (SOM), an unsupervised neural network methodology, to explore Internet dating data. The resulting visual maps are used to demonstrate the ability of SOMs to reveal interrelated parameters. The SOM process led to the emergence of correlations that were obscured in the original data and pointed to the role of what we call \'cultural age\' in the profiles and partnership preferences of the individuals. Our results suggest that the SOM approach offers a well established methodology that can be easily applied to complex sociological data sets. The SOM outcomes are discussed in relation to other research about identifying others and forming relationships in a network society.Self-Organising Map; Neural Network; Complex Data; Internet Dating; Age; Sex; Culture; Relationship; Visualisation

A Supporting Tool for Enhancing User’s Mental Model Elicitation and Decision-Making in User Experience Research

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Human–Computer Interaction on April 18, 2022, available at: https://doi.org/10.1080/10447318.2022.2041885User Experience (UX) research is intended to find insights and elicit applicable requirements to guide usable designs. Card Sorting is one of the most utilized methods. It is used to uncover the user's mental model and increase the usability of existing products. However, although Card Sorting has been widely utilized, most applications are based on spreadsheets. Furthermore, existing tools are principally intended to obtain qualitative information or customized quantitative outcomes to improve the information architecture. In this paper, a supporting tool based on the Card Sorting method is presented and detailed, including a comprehensive use case showing the main features. The tool implements predictive analysis of results through advanced statistics and machine learning techniques, providing comprehensive reports that enable evaluators and UX researchers to obtain high-level knowledge and important quantitative clues to enhance decision-making. The tool has been evaluated with participants and evaluators, obtaining relevant usability results and feedback.This work was partially supported by the Spanish Government under grant number RTI2018- 095255-B-I00]; and the Madrid Research Council under Grant number P2018/TCS-4314

Relatório de Estágio - Solução de BI Roaming Data Science (RoaDS) em ambiente Vodafone

A telecom company (Vodafone), had the need to implement a Business Intelligence solution for Roaming data across a wide set of different data sources. Based on the data visualization of this solution, its key users with decision power, can make a business analysis and needs of infrastructure and software expansion. This document aims to expose the scientific papers produced with the various stages of production of the solution (state of the art, architecture design and implementation results), this Business Intelligence solution was designed and implemented with OLAP methodologies and technologies in a Data Warehouse composed of Data Marts arranged in constellation, the visualization layer was custom made in JavaScript (VueJS). As a base for the results a questionnaire was created to be filled in by the key users of the solution. Based on this questionnaire it was possible to ascertain that user acceptance was satisfactory. The proposed objectives for the implementation of the BI solution with all the requirements was achieved with the infrastructure itself created from scratch in Kubernetes. This BI platform can be expanded using column storage databases created specifically with OLAP workloads in mind, removing the need for an OLAP cube layer. Based on Machine Learning algorithms, the platform will be able to perform the predictions needed to make decisions about Vodafone's Roaming infrastructure

Data visualization in yield component analysis: an expert study

Even though data visualization is a common analytical tool in numerous disciplines, it has rarely been used in agricultural sciences, particularly in agronomy. In this paper, we discuss a study on employing data visualization to analyze a multiplicative model. This model is often used by agronomists, for example in the so-called yield component analysis. The multiplicative model in agronomy is normally analyzed by statistical or related methods. In practice, unfortunately, usefulness of these methods is limited since they help to answer only a few questions, not allowing for a complex view of the phenomena studied. We believe that data visualization could be used for such complex analysis and presentation of the multiplicative model. To that end, we conducted an expert survey. It showed that visualization methods could indeed be useful for analysis and presentation of the multiplicative model

The role of motivation in regulating the extent to which data visualisation literacy influences business intelligence and analytics use in organisations

Dissertation (MCom (Informatics))--University of Pretoria 2022.The ability to read and interpret visualised data is a critical skill to have in this information age where business intelligence and analytics (BI&A) systems are increasingly used to support decision-making. Data visualisation literacy is seen as the foundation of analytics. Moreover, there is great hype about data-driven analytical culture and data democratisation, where users are encouraged to have wide access to data and fully use BI&A to reap the benefits. Motivation is a stimulant to the richer use of any information system (IS), yet literature provides a limited understanding of the evaluation of data visualisation literacy and the effect of motivation in the BI&A context. Thus, this study aims to explain the role of motivation in regulating the extent to which data visualisation literacy influences BI&A’s exploitative and explorative use in organisations. Data visualisation literacy is measured using six data visualisations that focus on the five cognitive basic intelligent analytical tasks that assess the user's ability to read and interpret visualised data. Two types of motivations are assessed using perceived enjoyment as an intrinsic motivator and perceived usefulness as an extrinsic motivator. The model is tested using quantitative data collected from 111 users, applying Structural Equation Modelling (SEM). The results indicate that intrinsic motivation exerts a positive effect on BI&A exploitative and explorative use while extrinsic motivation has a positive effect on BI&A exploitative use but weakens innovation with a negative effect on explorative use. The results further show an indirect relationship between data visualisation literacy with BI&A use through motivation. In addition, exploitation leads to creativity with exploitation positively being associated with exploration.InformaticsMCom (Informatics)Unrestricte

3D visualization of cadastre : assessing the suitability of visual variables and enhancement techniques in the 3D model of condominium property units

La visualisation 3D de données cadastrales a été exploitée dans de nombreuses études, car elle offre de nouvelles possibilités d’examiner des situations de supervision verticale des propriétés. Les chercheurs actifs dans ce domaine estiment que la visualisation 3D pourrait fournir aux utilisateurs une compréhension plus intuitive d’une situation où des propriétés se superposent, ainsi qu’une plus grande capacité et avec moins d’ambiguïté de montrer des problèmes potentiels de chevauchement des unités de propriété. Cependant, la visualisation 3D est une approche qui apporte de nombreux défis par rapport à la visualisation 2D. Les précédentes recherches effectuées en cadastre 3D, et qui utilisent la visualisation 3D, ont très peu enquêté l’impact du choix des variables visuelles (ex. couleur, style) sur la prise de décision. Dans l’optique d'améliorer la visualisation 3D de données cadastres, cette thèse de doctorat examine l’adéquation du choix des variables visuelles et des techniques de rehaussement associées afin de produire un modèle de condominium 3D optimal, et ce, en fonction de certaines tâches spécifiques de visualisation. Les tâches visées sont celles dédiées à la compréhension dans l’espace 3D des limites de propriété du condominium. En ce sens, ce sont principalement des tâches notariales qui ont été ciblées. De plus, cette thèse va mettre en lumière les différences de l’impact des variables visuelles entre une visualisation 2D et 3D. Cette thèse identifie dans un premier temps un cadre théorique pour l'interprétation des variables visuelles dans le contexte d’une visualisation 3D et de données cadastrales au regard d’une revue de littéraire. Dans un deuxième temps, des expérimentations ont été réalisées afin de mettre à l’épreuve la performance des variables visuelles (ex. couleur, valeur, texture) et des techniques de rehaussement (transparence, annotation, déplacement). Trois approches distinctes ont été utilisées : 1) discussion directe avec des personnes œuvrant en géomatique, 2) entrevue face à face avec des notaires et 3) questionnaire en ligne avec des groupes ciblés. L’utilisabilité mesurée en termes d’efficacité, d’efficience et de degré de satisfaction a servi aux comparaisons des expérimentations. Les principaux résultats de cette recherche sont : 1) Une liste de tâches visuelles notariales utiles à la délimitation des unités de propriété dans le contexte de la visualisation 3D de condominium ; 2) Des recommandations quant à l'adéquation de huit variables visuelles et de trois techniques de rehaussement afin d’optimiser la réalisation d’un certain nombre de tâches notariales ; 3) Une analyse comparative de la performance de ces variables entre une visualisation 2D et 3D.3D visualization is being widely used in GIS (geographic information system) and CAD (computer-aided design) applications. It has also been introduced in cadastre studies to better communicate overlaps to the viewer, where the property units vertically stretch over or cover one part of the land parcel. Researchers believe that 3D visualization could provide viewers with a more intuitive perception, and it has the capability to demonstrate overlapping property units in condominiums unambiguously. However, 3D visualization has many challenges compared with 2D visualization. Many cadastre researchers adopted 3D visualization without thoroughly investigating the potential users, the visual tasks for decision-making, and the appropriateness of their representation design. Neither designers nor users may be aware of the risk of producing an inadequate 3D visualization, especially in an era when 3D visualization is relatively novel in the cadastre domain. With a general aim to improve the 3D visualization of cadastre data, this dissertation addresses the design of the 3D cadastre model from a graphics semiotics viewpoint including visual variables and enhancement techniques. The research questions are, firstly, what is the suitability of the visual variables and enhancement techniques in the 3D cadastre model to support the intended users' decision-making goal of delimitating condominium property units, and secondly, what are the perceptual properties of visual variables in 3D visualization compared with 2D visualization? This dissertation firstly identifies the theoretical framework for the interpretation of visual variables in 3D visualization as well as cadastre-related knowledge with literature review. Then, we carry out a preliminary evaluation of the feasibility of visual variables and enhancement techniques in a form of an expert-group review. With the result of the preliminary evaluation, this research then performs the hypothetico-deductive scientific approach to establishing a list of hypotheses to be validated by empirical tests regarding the suitability of visual variables and enhancement techniques in a cartographic representation of property units in condominiums for 3D visualization. The evaluation is based on the usability specification, which contains three measurements: effectiveness, efficiency, and preference. Several empirical tests are conducted with cadastral users in the forms of face-to-face interviews and online questionnaires, followed by statistical analysis. Size, shape, brightness, saturation, hue, orientation, texture, and transparency are the most discussed and used visual variables in existing cartographic research and implementations; thus, these eight visual variables have been involved in the tests. Their perceptual properties exhibited in the empirical test with concrete 3D models in this work are compared with those in a 2D visualization, which is derived from a literature-based synthesis. Three enhancement techniques, including labeling, 3D explosion, and highlighting, are tested as well. There are three main outcomes of this work. First, we established a list of visual tasks adapted to notaries for delimiting property units in the context of 3D visualization of condominium cadastres. Second, we describe the suitability of eight visual variables (Size, Shape, Brightness, Saturation, Hue, Orientation, Texture, and Transparency) of the property units and three enhancement techniques (labeling, 3D explosion and highlighting) in the context of 3D visualisation of condominium property units, based on the usability specification for delimitating visual tasks. For example, brightness only shows good performance in helping users distinguish private and common parts in the context of 3D visualization of property units in condominiums. As well, color hue and saturation are effective and preferable. The third outcome is a statement of the perceptual properties’ differences of visual variables between 3D visualization and 2D visualization. For example, according to Bertin (1983)’s definition, orientation is associative and selective in 2D, yet it does not perform in a 3D visualization. In addition, 3D visualization affects the performance of brightness, making it marginally dissociative and selective

The application of software visualization technology to evolutionary computation: a case study in Genetic Algorithms

Evolutionary computation is an area within the field of artificial intelligence that is founded upon the principles of biological evolution. Evolution can be defined as the process of gradual development. Evolutionary algorithms are typically applied as a generic problem solving method, searching a problem space in order to locate good solutions. These solutions are found through an iterative evolutionary search that progresses by means of gradual developments. In the majority of cases of evolutionary computation the user is not aware of their algorithm's search behaviour. This causes two problems. First, the user has no way of assuring the quality of any solutions found other than to compare the solutions found by the algorithm with any available benchmark solutions or to re-run the algorithm and check if the results can be repeated or improved upon. Second, because the user is unaware of the algorithm's behaviour they have no way of identifying the contribution of the different components of the algorithm and therefore, no direct way of analyzing the algorithm's design and assigning credit to good algorithm components, or locating and improving ineffective algorithm components. The artificial intelligence and engineering communities have been slow to accept evolutionary computation as a robust problem-solving method because, unlike cased-based systems, rule-based systems or belief networks, they are unable to follow the algorithm's reasoning when locating a set of solutions in the problem space. During an evolutionary algorithm's execution the user may be able to see the results of the search but the search process itself like is a "black box" to the user. It is the search behaviour of evolutionary algorithms that needs to be understood by the user, in order for evolutionary computation to become more accepted within these communities. The aim of software visualization is to help people understand and use computer software. Software visualization technology has been applied successfully to illustrate a variety of heuristic search algorithms, programming languages and data structures. This thesis adopts software visualization as an approach for illustrating the search behaviour of evolutionary algorithms. Genetic Algorithms ("GAs") are used here as a specific case study to illustrate how software visualization may be applied to evolutionary computation. A set of visualization requirements are derived from the findings of a GA user study. A number of search space visualization techniques are examined for illustrating the search behaviour of a GA. "Henson," an extendable framework for developing visualization tools for genetic algorithms is presented. Finally, the application of the Henson framework is illustrated by the development of "Gonzo," a visualization tool designed to enable GA users to explore their algorithm's search behaviour. The contributions made in this thesis extend into the areas of software visualization, evolutionary computation and the psychology of programming. The GA user study presented here is the first and only known study of the working practices of GA users. The search space visualization techniques proposed here have never been applied in this domain before, and the resulting interactive visualizations provide the GA user with a previously unavailable insight into their algorithm's operation