Symmetric Synchronous Collaborative Navigation

Synchronous collaborative navigation is a form of social navigation where users virtually share a web browser. In this paper, we present a symmetric, proxy-based architecture where each user can take the lead and guide others in visiting web sites, without the need for a special browser or other software. We show how we have applied this scheme to a problem-solving-oriented e-learning system

DIVERSE: a Software Toolkit to Integrate Distributed Simulations with Heterogeneous Virtual Environments

We present DIVERSE (Device Independent Virtual Environments- Reconfigurable, Scalable, Extensible), which is a modular collection of complimentary software packages that we have developed to facilitate the creation of distributed operator-in-the-loop simulations. In DIVERSE we introduce a novel implementation of remote shared memory (distributed shared memory) that uses Internet Protocol (IP) networks. We also introduce a new method that automatically extends hardware drivers (not in the operating system kernel driver sense) into inter-process and Internet hardware services. Using DIVERSE, a program can display in a CAVE™, ImmersaDesk™, head mounted display (HMD), desktop or laptop without modification. We have developed a method of configuring user programs at run-time by loading dynamic shared objects (DSOs), in contrast to the more common practice of creating interpreted configuration languages. We find that by loading DSOs the development time, complexity and size of DIVERSE and DIVERSE user applications is significantly reduced. Configurations to support different I/O devices, device emulators, visual displays, and any component of a user application including interaction techniques, can be changed at run-time by loading different sets of DIVERSE DSOs. In addition, interpreted run-time configuration parsers have been implemented using DIVERSE DSOs; new ones can be created as needed. DIVERSE is free software, licensed under the terms of the GNU General Public License (GPL) and the GNU Lesser General Public License (LGPL) licenses. We describe the DIVERSE architecture and demonstrate how DIVERSE was used in the development of a specific application, an operator-in-the-loop Navy ship-board crane simulator, which runs unmodified on a desktop computer and/or in a CAVE with motion base motion queuing

Conceitos e métodos para apoio ao desenvolvimento e avaliação de colaboração remota utilizando realidade aumentada

Remote Collaboration using Augmented Reality (AR) shows great potential to establish a common ground in physically distributed scenarios where team-members need to achieve a shared goal. However, most research efforts in this field have been devoted to experiment with the enabling technology and propose methods to support its development. As the field evolves, evaluation and characterization of the collaborative process become an essential, but difficult endeavor, to better understand the contributions of AR. In this thesis, we conducted a critical analysis to identify the main limitations and opportunities of the field, while situating its maturity and proposing a roadmap of important research actions. Next, a human-centered design methodology was adopted, involving industrial partners to probe how AR could support their needs during remote maintenance. These outcomes were combined with literature methods into an AR-prototype and its evaluation was performed through a user study. From this, it became clear the necessity to perform a deep reflection in order to better understand the dimensions that influence and must/should be considered in Collaborative AR. Hence, a conceptual model and a humancentered taxonomy were proposed to foster systematization of perspectives. Based on the model proposed, an evaluation framework for contextualized data gathering and analysis was developed, allowing support the design and performance of distributed evaluations in a more informed and complete manner. To instantiate this vision, the CAPTURE toolkit was created, providing an additional perspective based on selected dimensions of collaboration and pre-defined measurements to obtain “in situ” data about them, which can be analyzed using an integrated visualization dashboard. The toolkit successfully supported evaluations of several team-members during tasks of remote maintenance mediated by AR. Thus, showing its versatility and potential in eliciting a comprehensive characterization of the added value of AR in real-life situations, establishing itself as a generalpurpose solution, potentially applicable to a wider range of collaborative scenarios.Colaboração Remota utilizando Realidade Aumentada (RA) apresenta um enorme potencial para estabelecer um entendimento comum em cenários onde membros de uma equipa fisicamente distribuídos precisam de atingir um objetivo comum. No entanto, a maioria dos esforços de investigação tem-se focado nos aspetos tecnológicos, em fazer experiências e propor métodos para apoiar seu desenvolvimento. À medida que a área evolui, a avaliação e caracterização do processo colaborativo tornam-se um esforço essencial, mas difícil, para compreender as contribuições da RA. Nesta dissertação, realizámos uma análise crítica para identificar as principais limitações e oportunidades da área, ao mesmo tempo em que situámos a sua maturidade e propomos um mapa com direções de investigação importantes. De seguida, foi adotada uma metodologia de Design Centrado no Humano, envolvendo parceiros industriais de forma a compreender como a RA poderia responder às suas necessidades em manutenção remota. Estes resultados foram combinados com métodos da literatura num protótipo de RA e a sua avaliação foi realizada com um caso de estudo. Ficou então clara a necessidade de realizar uma reflexão profunda para melhor compreender as dimensões que influenciam e devem ser consideradas na RA Colaborativa. Foram então propostos um modelo conceptual e uma taxonomia centrada no ser humano para promover a sistematização de perspetivas. Com base no modelo proposto, foi desenvolvido um framework de avaliação para recolha e análise de dados contextualizados, permitindo apoiar o desenho e a realização de avaliações distribuídas de forma mais informada e completa. Para instanciar esta visão, o CAPTURE toolkit foi criado, fornecendo uma perspetiva adicional com base em dimensões de colaboração e medidas predefinidas para obter dados in situ, que podem ser analisados utilizando o painel de visualização integrado. O toolkit permitiu avaliar com sucesso vários colaboradores durante a realização de tarefas de manutenção remota apoiada por RA, permitindo mostrar a sua versatilidade e potencial em obter uma caracterização abrangente do valor acrescentado da RA em situações da vida real. Sendo assim, estabelece-se como uma solução genérica, potencialmente aplicável a uma gama diversificada de cenários colaborativos.Programa Doutoral em Engenharia Informátic

Vehicle infrastructure cooperative localization using Factor Graphs

Highly assisted and Autonomous Driving is dependent on the accurate localization of both the vehicle and other targets within the environment. With increasing traffic on roads and wider proliferation of low cost sensors, a vehicle-infrastructure cooperative localization scenario can provide improved performance over traditional mono-platform localization. The paper highlights the various challenges in the process and proposes a solution based on Factor Graphs which utilizes the concept of topology of vehicles. A Factor Graph represents probabilistic graphical model as a bipartite graph. It is used to add the inter-vehicle distance as constraints while localizing the vehicle. The proposed solution is easily scalable for many vehicles without increasing the execution complexity. Finally simulation indicates that incorporating the topology information as a state estimate can improve performance over the traditional Kalman Filter approac

KInNeSS: A Modular Framework for Computational Neuroscience

Making use of very detailed neurophysiological, anatomical, and behavioral data to build biological-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalabiltiy, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multu-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions of ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further developement of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effecitively collaborate using a modern neural simulation platform.Center for Excellence for Learning Education, Science, and Technology (SBE-0354378); Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

Ontology reasoning using SPARQL query: A case study of e-learning usage

The involvement of learning pedagogy towards implementation of e-learning contribute to the additional values, and it is assign as a benchmark when the investigation and evaluation will carry out. The results obtained later believed would be fit to the domain problem.The results might provide instructional theories including recommendation after reasoning that can be used to improve the quality of teaching and learning in the virtual classroom. Ontology as formal conceptualization has been chosen as research methodology. Ontology conceptualization helps to illustrate the e-learning usage including activities and actions, likewise learning pedagogy in the form of concepts, class, relationships and instances. The ontology constructed in this paper is used in conjunction with the SPARQL rules, which are designed to test the reasoning ability of ontology. Reasoning results should be able to describe the knowledge contained in ontology, as well the facts on it. The SPARQL rules contains triplets to verify if the students are actively engaged in a meaningful way towards e-learning usage. The backward engine is optimized to store the facts obtained from queries. Development of ontology knowledge based and reasoning rules with SPARQL queries allow to contribute a sustainable competitive advantages regarding the e-learning utilization. Eventually, this research produced a learning ontology with reasoning capability to get meaningful information