929 resultados para human-computer visualization
Resumo:
Brain computer interface (BCI) is a kind of human machine interface, which provides a new interaction method between human and computer or other equipment. The most significant characteristic of BCI system is that its control input is brain electrical activities acquired from the brain instead of traditional input such as hands or eyes. BCI technique has rapidly developed during last two decades and it has mainly worked as an auxiliary technique to help the disable people improve their life qualities. With the appearance of low cost novel electrical devices such as EMOTIV, BCI technique has been applied to the general public through many useful applications including video gaming, virtual reality and virtual keyboard. The purpose of this research is to be familiar with EMOTIV EPOC system and make use of it to build an EEG based BCI system for controlling an industrial manipulator by means of human thought. To build a BCI system, an acquisition program based on EMOTIV EPOC system is designed and a MFC based dialog that works as an operation panel is presented. Furthermore, the inverse kinematics of RV-3SB industrial robot was solved. In the last part of this research, the designed BCI system with human thought input is examined and the results indicate that the system is running smoothly and displays clearly the motion type and the incremental displacement of the motion.
Resumo:
The computer game industry has grown steadily for years, and in revenues it can be compared to the music and film industries. The game industry has been moving to digital distribution. Computer gaming and the concept of business model are discussed among industrial practitioners and the scientific community. The significance of the business model concept has increased in the scientific literature recently, although there is still a lot of discussion going on on the concept. In the thesis, the role of the business model in the computer game industry is studied. Computer game developers, designers, project managers and organization leaders in 11 computer game companies were interviewed. The data was analyzed to identify the important elements of computer game business model, how the business model concept is perceived and how the growth of the organization affects the business model. It was identified that the importance of human capital is crucial to the business. As games are partly a product of creative thinking also innovation and the creative process are highly valued. The same applies to technical skills when performing various activities. Marketing and customer relationships are also considered as key elements in the computer game business model. Financing and partners are important especially for startups, when the organization is dependent on external funding and third party assets. The results of this study provide organizations with improved understanding on how the organization is built and what business model elements are weighted.
Resumo:
Human-Centered Design (HCD) is a well-recognized approach to the design of interactive computing systems that supports everyday and professional lives of people. To that end, the HCD approach put central emphasis on the explicit understanding of users and context of use by involving users throughout the entire design and development process. With mobile computing, the diversity of users as well as the variety in the spatial, temporal, and social settings of the context of use has notably expanded, which affect the effort of interaction designers to understand users and context of use. The emergence of the mobile apps era in 2008 as a result of structural changes in the mobile industry and the profound enhanced capabilities of mobile devices, further intensify the embeddedness of technology in the daily life of people and the challenges that interaction designers face to cost-efficiently understand users and context of use. Supporting interaction designers in this challenge requires understanding of their existing practice, rationality, and work environment. The main objective of this dissertation is to contribute to interaction design theories by generating understanding on the HCD practice of mobile systems in the mobile apps era, as well as to explain the rationality of interaction designers in attending to users and context of use. To achieve that, a literature study is carried out, followed by a mixed-methods research that combines multiple qualitative interview studies and a quantitative questionnaire study. The dissertation contributes new insights regarding the evolving HCD practice at an important time of transition from stationary computing to mobile computing. Firstly, a gap is identified between interaction design as practiced in research and in the industry regarding the involvement of users in context; whereas the utilization of field evaluations, i.e. in real-life environments, has become more common in academic projects, interaction designers in the industry still rely, by large, on lab evaluations. Secondly, the findings indicate on new aspects that can explain this gap and the rationality of interaction designers in the industry in attending to users and context; essentially, the professional-client relationship was found to inhibit the involvement of users, while the mental distance between practitioners and users as well as the perceived innovativeness of the designed system are suggested in explaining the inclination to study users in situ. Thirdly, the research contributes the first explanatory model on the relation between the organizational context and HCD; essentially, innovation-focused organizational strategies greatly affect the cost-effective usage of data on users and context of use. Last, the findings suggest a change in the nature of HCD in the mobile apps era, at least with universal consumer systems; evidently, the central attention on the explicit understanding of users and context of use shifts from an early requirements phase and continual activities during design and development to follow-up activities. That is, the main effort to understand users is by collecting data on their actual usage of the system, either before or after the system is deployed. The findings inform both researchers and practitioners in interaction design. In particular, the dissertation suggest on action research as a useful approach to support interaction designers and further inform theories on interaction design. With regard to the interaction design practice, the dissertation highlights strategies that encourage a more cost-effective user- and context-informed interaction design process. With the continual embeddedness of computing into people’s life, e.g. with wearable devices and connected car systems, the dissertation provides a timely and valuable view on the evolving humancentered design.
Resumo:
Affiliation: Pascal Michel : Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal
Resumo:
Le développement du logiciel actuel doit faire face de plus en plus à la complexité de programmes gigantesques, élaborés et maintenus par de grandes équipes réparties dans divers lieux. Dans ses tâches régulières, chaque intervenant peut avoir à répondre à des questions variées en tirant des informations de sources diverses. Pour améliorer le rendement global du développement, nous proposons d'intégrer dans un IDE populaire (Eclipse) notre nouvel outil de visualisation (VERSO) qui calcule, organise, affiche et permet de naviguer dans les informations de façon cohérente, efficace et intuitive, afin de bénéficier du système visuel humain dans l'exploration de données variées. Nous proposons une structuration des informations selon trois axes : (1) le contexte (qualité, contrôle de version, bogues, etc.) détermine le type des informations ; (2) le niveau de granularité (ligne de code, méthode, classe, paquetage) dérive les informations au niveau de détails adéquat ; et (3) l'évolution extrait les informations de la version du logiciel désirée. Chaque vue du logiciel correspond à une coordonnée discrète selon ces trois axes, et nous portons une attention toute particulière à la cohérence en naviguant entre des vues adjacentes seulement, et ce, afin de diminuer la charge cognitive de recherches pour répondre aux questions des utilisateurs. Deux expériences valident l'intérêt de notre approche intégrée dans des tâches représentatives. Elles permettent de croire qu'un accès à diverses informations présentées de façon graphique et cohérente devrait grandement aider le développement du logiciel contemporain.
Resumo:
L’objectif de cette thèse par articles est de présenter modestement quelques étapes du parcours qui mènera (on espère) à une solution générale du problème de l’intelligence artificielle. Cette thèse contient quatre articles qui présentent chacun une différente nouvelle méthode d’inférence perceptive en utilisant l’apprentissage machine et, plus particulièrement, les réseaux neuronaux profonds. Chacun de ces documents met en évidence l’utilité de sa méthode proposée dans le cadre d’une tâche de vision par ordinateur. Ces méthodes sont applicables dans un contexte plus général, et dans certains cas elles on tété appliquées ailleurs, mais ceci ne sera pas abordé dans le contexte de cette de thèse. Dans le premier article, nous présentons deux nouveaux algorithmes d’inférence variationelle pour le modèle génératif d’images appelé codage parcimonieux “spike- and-slab” (CPSS). Ces méthodes d’inférence plus rapides nous permettent d’utiliser des modèles CPSS de tailles beaucoup plus grandes qu’auparavant. Nous démontrons qu’elles sont meilleures pour extraire des détecteur de caractéristiques quand très peu d’exemples étiquetés sont disponibles pour l’entraînement. Partant d’un modèle CPSS, nous construisons ensuite une architecture profonde, la machine de Boltzmann profonde partiellement dirigée (MBP-PD). Ce modèle a été conçu de manière à simplifier d’entraînement des machines de Boltzmann profondes qui nécessitent normalement une phase de pré-entraînement glouton pour chaque couche. Ce problème est réglé dans une certaine mesure, mais le coût d’inférence dans le nouveau modèle est relativement trop élevé pour permettre de l’utiliser de manière pratique. Dans le deuxième article, nous revenons au problème d’entraînement joint de machines de Boltzmann profondes. Cette fois, au lieu de changer de famille de modèles, nous introduisons un nouveau critère d’entraînement qui donne naissance aux machines de Boltzmann profondes à multiples prédictions (MBP-MP). Les MBP-MP sont entraînables en une seule étape et ont un meilleur taux de succès en classification que les MBP classiques. Elles s’entraînent aussi avec des méthodes variationelles standard au lieu de nécessiter un classificateur discriminant pour obtenir un bon taux de succès en classification. Par contre, un des inconvénients de tels modèles est leur incapacité de générer deséchantillons, mais ceci n’est pas trop grave puisque la performance de classification des machines de Boltzmann profondes n’est plus une priorité étant donné les dernières avancées en apprentissage supervisé. Malgré cela, les MBP-MP demeurent intéressantes parce qu’elles sont capable d’accomplir certaines tâches que des modèles purement supervisés ne peuvent pas faire, telles que celle de classifier des données incomplètes ou encore celle de combler intelligemment l’information manquante dans ces données incomplètes. Le travail présenté dans cette thèse s’est déroulé au milieu d’une période de transformations importantes du domaine de l’apprentissage à réseaux neuronaux profonds qui a été déclenchée par la découverte de l’algorithme de “dropout” par Geoffrey Hinton. Dropout rend possible un entraînement purement supervisé d’architectures de propagation unidirectionnel sans être exposé au danger de sur- entraînement. Le troisième article présenté dans cette thèse introduit une nouvelle fonction d’activation spécialement con ̧cue pour aller avec l’algorithme de Dropout. Cette fonction d’activation, appelée maxout, permet l’utilisation de aggrégation multi-canal dans un contexte d’apprentissage purement supervisé. Nous démontrons comment plusieurs tâches de reconnaissance d’objets sont mieux accomplies par l’utilisation de maxout. Pour terminer, sont présentons un vrai cas d’utilisation dans l’industrie pour la transcription d’adresses de maisons à plusieurs chiffres. En combinant maxout avec une nouvelle sorte de couche de sortie pour des réseaux neuronaux de convolution, nous démontrons qu’il est possible d’atteindre un taux de succès comparable à celui des humains sur un ensemble de données coriace constitué de photos prises par les voitures de Google. Ce système a été déployé avec succès chez Google pour lire environ cent million d’adresses de maisons.
Resumo:
This paper presents a lattice-based visual metaphor for knowledge discovery in electronic mail. It allows a user to navigate email using a visual lattice metaphor rather than a tree structure. By using such a conceptual multi-hierarchy, the content and shape of the lattice can be varied to accommodate any number of queries against the email collection. The system provides more flexibility in retrieving stored emails and can be generalised to any electronic documents. The paper presents the underlying mathematical structures, and a number of examples of the lattice and multi-hierarchy working with a prototypical email collection.
Resumo:
In this paper, we describe an interdisciplinary project in which visualization techniques were developed for and applied to scholarly work from literary studies. The aim was to bring Christof Schöch's electronic edition of Bérardier de Bataut's Essai sur le récit (1776) to the web. This edition is based on the Text Encoding Initiative's XML-based encoding scheme (TEI P5, subset TEI-Lite). This now de facto standard applies to machine-readable texts used chiefly in the humanities and social sciences. The intention of this edition is to make the edited text freely available on the web, to allow for alternative text views (here original and modern/corrected text), to ensure reader-friendly annotation and navigation, to permit on-line collaboration in encoding and annotation as well as user comments, all in an open source, generically usable, lightweight package. These aims were attained by relying on a GPL-based, public domain CMS (Drupal) and combining it with XSL-Stylesheets and Java Script.
Resumo:
Vorgestellt wird eine weltweit neue Methode, Schnittstellen zwischen Menschen und Maschinen für individuelle Bediener anzupassen. Durch Anwenden von Abstraktionen evolutionärer Mechanismen wie Selektion, Rekombination und Mutation in der EOGUI-Methodik (Evolutionary Optimization of Graphical User Interfaces) kann eine rechnergestützte Umsetzung der Methode für Graphische Bedienoberflächen, insbesondere für industrielle Prozesse, bereitgestellt werden. In die Evolutionäre Optimierung fließen sowohl die objektiven, d.h. messbaren Größen wie Auswahlhäufigkeiten und -zeiten, mit ein, als auch das anhand von Online-Fragebögen erfasste subjektive Empfinden der Bediener. Auf diese Weise wird die Visualisierung von Systemen den Bedürfnissen und Präferenzen einzelner Bedienern angepasst. Im Rahmen dieser Arbeit kann der Bediener aus vier Bedienoberflächen unterschiedlicher Abstraktionsgrade für den Beispielprozess MIPS ( MIschungsProzess-Simulation) die Objekte auswählen, die ihn bei der Prozessführung am besten unterstützen. Über den EOGUI-Algorithmus werden diese Objekte ausgewählt, ggf. verändert und in einer neuen, dem Bediener angepassten graphischen Bedienoberfläche zusammengefasst. Unter Verwendung des MIPS-Prozesses wurden Experimente mit der EOGUI-Methodik durchgeführt, um die Anwendbarkeit, Akzeptanz und Wirksamkeit der Methode für die Führung industrieller Prozesse zu überprüfen. Anhand der Untersuchungen kann zu großen Teilen gezeigt werden, dass die entwickelte Methodik zur Evolutionären Optimierung von Mensch-Maschine-Schnittstellen industrielle Prozessvisualisierungen tatsächlich an den einzelnen Bediener anpaßt und die Prozessführung verbessert.
Resumo:
Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.
Resumo:
A method is presented for the visual analysis of objects by computer. It is particularly well suited for opaque objects with smoothly curved surfaces. The method extracts information about the object's surface properties, including measures of its specularity, texture, and regularity. It also aids in determining the object's shape. The application of this method to a simple recognition task ??e recognition of fruit ?? discussed. The results on a more complex smoothly curved object, a human face, are also considered.
Resumo:
The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study
Resumo:
How do resource booms affect human capital accumulation? We exploit time and spatial variation generated by the commodity boom across local governments in Peru to measure the effect of natural resources on human capital formation. We explore the effect of both mining production and tax revenues on test scores, finding a substantial and statistically significant effect for the latter. Transfers to local governments from mining tax revenues are linked to an increase in math test scores of around 0.23 standard deviations. We find that the hiring of permanent teachers as well as the increases in parental employment and improvements in health outcomes of adults and children are plausible mechanisms for such large effect on learning. These findings suggest that redistributive policies could facilitate the accumulation of human capital in resource abundant developing countries as a way to avoid the natural resources curse.
Resumo:
Eye tracking has become a preponderant technique in the evaluation of user interaction and behaviour with study objects in defined contexts. Common eye tracking related data representation techniques offer valuable input regarding user interaction and eye gaze behaviour, namely through fixations and saccades measurement. However, these and other techniques may be insufficient for the representation of acquired data in specific studies, namely because of the complexity of the study object being analysed. This paper intends to contribute with a summary of data representation and information visualization techniques used in data analysis within different contexts (advertising, websites, television news and video games). Additionally, several methodological approaches are presented in this paper, which resulted from several studies developed and under development at CETAC.MEDIA - Communication Sciences and Technologies Research Centre. In the studies described, traditional data representation techniques were insufficient. As a result, new approaches were necessary and therefore, new forms of representing data, based on common techniques were developed with the objective of improving communication and information strategies. In each of these studies, a brief summary of the contribution to their respective area will be presented, as well as the data representation techniques used and some of the acquired results.
Resumo:
GODIVA2 is a dynamic website that provides visual access to several terabytes of physically distributed, four-dimensional environmental data. It allows users to explore large datasets interactively without the need to install new software or download and understand complex data. Through the use of open international standards, GODIVA2 maintains a high level of interoperability with third-party systems, allowing diverse datasets to be mutually compared. Scientists can use the system to search for features in large datasets and to diagnose the output from numerical simulations and data processing algorithms. Data providers around Europe have adopted GODIVA2 as an INSPIRE-compliant dynamic quick-view system for providing visual access to their data.