Augmenting 3D virtual environments (3DVEs) with additional abstract information, with different data types (such as numbers, texts, images and videos) amplifies and enhances the user's spatial cognition and understanding of geometrical objects in order to perform specific tasks which require both abstract information and a 3D scene. Many interactive information visualization techniques have been created to incorporate abstract information into 3DVEs. The designers of 3DVEs are faced with the challenge of selecting a specific information visualization technique or creating a novel technique according to their specific design needs and contexts. Therefore, a toolkit for the usability evaluation is needed to help them compare the usability of different information visualization techniques according to specific design needs and contexts. Our main objective is to create such toolkit for performing usability tests in order to complete a reusable evaluation grid for comparing the usability of visualization techniques in different evaluation contexts. In this article, we present an evaluation framework and toolkit that we have developed in order to perform usability tests.
Abstract information refers to information that a user can't directly obtain just by visualizing the spatial information of objects in a 3D virtual environment (3DVE). This thesis first reviews the state of the art on interactive 3DVEs development, abstract information visualization techniques and the evaluation of interactive 3DVEs. Then, this thesis presents a conceptual model, reusable toolkit and usability evaluation methodology for comparing the usability of different abstract information visualization techniques. In order to control the navigation skill variable, the design of a constrained navigation approach for teleporting the user from one user context to another is proposed. Finally, this thesis presents case studies for validating the proposed conceptual model, toolkit and usability evaluation methodology by performing usability testing experiments. The contributions of this thesis are a conceptual model, reusable toolkit and usability evaluation methodology for measuring and comparing the usability of abstract information visualization techniques in interactive 3DVEs.
We propose the extraction of musculoskeletal structures (bones, muscles) from the lower limb, following three main objectives: development of an MRI protocol, processing and labelling of the image data, and the exploitation of multi-channel data during the segmentation of individual muscles. We propose an MR acquisition protocol that generates seamless, high-resolution images of thigh and calf. We present a method to identify air and muscle tissue in the image and massively parallel version of the approach. To identify the individual muscles, we align a muscle template which is modified with our deformable model framework under the influence of image forces to match the actual anatomy. This iterative process uses multi-channel image data to find relevant image features. We propose coupled multi-resolution deformable models that allow working on different resolutions in parallel. This work is aimed at helping the understanding of diseases by providing personalised anatomical models.
The thesis proposes an interdisciplinary framework for service research in information systems that goes beyond the technological concerns and integrates the business concerns about service processes and models and the user's concerns about service usage and value. Based on this framework, the thesis analyzes further the concept of service value and suggests the value perspective in the analysis and design of service systems. In addition, the thesis analyses the role of the user in service systems and suggests a method for service analysis and design that emphasises on the use of service by the user. The research outcomes can provide several research implications and insights and can inspire various potential uses, especially in research projects that seek to integrate a variety of technologies and services with the purpose to facilitate and enable people in their daily life practices.
The human knee joint is the largest and most complex joint of the human body. The interdependencies encountered in the musculoskeletal system are crucial in understanding musculoskeletal conditions. Patient-specific models are promising methods to unravel clinical diagnosis. However, as the range of medical and experimental data is expanding, it has become a challenge to integrate data in virtual models in a way that it is comprehensive and reliable for medical diagnosis. In this thesis, we focus on a novel modelling paradigms that encompasses mechanics with microscale and physiological data which aims at being practical for clinical investigation. We integrate microstructural and physiological data into articulation simulations, by investigating different biological organization levels such as organ, tissue, cellular, and molecular level. We consider synergies between in vitro data, medical imaging data and computational models, which can have a significant impact on the development of realistic simulation tools to answer clinical challenges.
Smart mobile services and applications use users' context. However, we never investigate how users perceive this context and how to leverage this perception for even smarter services. We represent the perception of the context of users as their intimacy, their familiarity with their current place, the number, and kind of people around them. The adjective ‘intimate' describes the context as familiar, being private and comfortable. First, we validate the intimacy concept. We establish that users use mobile services differently in different intimacy situations, and we create a first theoretical model to estimate their intimacy. Second, we investigate the intimacy predictability in practice (limitations and solutions). Finally, we show how we can leverage intimacy for studies on users' context or deploy our intimacy model to help apps developer. Advertisers can use it to deliver their content, and it can support the innovative projects, as Google Project Tango, to get smarter.
Multiple tasks related to documents, such as indexing, retrieving, annotation, or translation are based on linguistic, terminological and ontological knowledge existing in resources of different types represented using various formalisms. Building bridges between these resources and using them together is a complex task. Solving this problem relies on finding the right resources before extracting the required data. Ontology repositories have been created to help in this task by collecting ontologies and offering effective indexing of these resources. However, these repositories treat a single category of resources and do not provide operations for generating new resources. To meet these needs in terms of knowledge engineering, our contributions are (1) an ontology for representing heterogeneous resources and knowledge combination operators; (2) an approach based on the principles of semantic web to ensure the representation, storage and alignment of heterogeneous resources and (3) the development of an ontology-based repository for combining alignment resources.
When scientists are looking for information in document collections, they generally have a precise objective in mind. They try to answer specific needs such as finding the definition of a concept, checking whether an idea has already been tested, or comparing the scientific conclusions of several documents. To build better information system model it is important to understand the needs of scientists in terms of information and their seeking information behaviour. The contributions of this thesis are to a) offer a user model; b) propose a generic annotation model (SciAnnotDoc) for scientific documents; c) demonstrate that the annotation model is realistic enough to be used by both manual and automatic methods of annotation; d) build a faceted search interface (FSAD) and e) evaluate the model with scientists and show that the FSAD interface is more effective than a keywords-search, notably in terms of user preference, recall and F1 measure.
In cloud computing, service resources are distributed. Cloud service markets respond simultaneously to multiple, remote customers. Every customer needs to agree with a service level agreement (SLA) to lease a new service. SLAs represent contractual terms and conditions between service providers and customers. SLA information can be complex due to the diversity and plethora of offered cloud services. Cloud SLAs lack standardization, which would motivate their automated and consistent processing. We propose the systematic management of SLA information through an SLA graph data model. The SLA graph is positioned in the cloud computing setting, where services are provisioned on-demand. We analyze how flexibly the proposed SLA graph integrates data elements and relationships that are specified by diverse business domains. The SLA graph model supports the data exchange over connected environments and endorses SLA unification and standardization efforts for cloud computing services.
The main challenge for steering IS evolution is to cope with the uncertainty inherent to any IS change, while taking into consideration its complexity due to the entanglement of its multiple dimensions: regulation, information, activity and technology. We observe that i) steering IS evolution requires understanding its IS domain, ii) its impacts are difficult to predict and iii) the guidance for IS evolution steering is almost nonexistent. Consequently, the main goal of this thesis is to provide an approach to reduce uncertainty by exploiting the information available in the IS and by considering its multiple dimensions. In particular, we intend to reach four interrelated sub-goals: 1) to propose a steering information kernel which integrates the multiple IS dimensions into one model, 2) to provide a generic model of IS evolution, 3) to provide analysis perspectives for the evolution and 4) to provide guidance for IS evolution steering.
