71,896 research outputs found

    Multimodal agent interfaces and system architectures for health and fitness companions

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    Multimodal conversational spoken dialogues using physical and virtual agents provide a potential interface to motivate and support users in the domain of health and fitness. In this paper we present how such multimodal conversational Companions can be implemented to support their owners in various pervasive and mobile settings. In particular, we focus on different forms of multimodality and system architectures for such interfaces

    CernVM Online and Cloud Gateway: a uniform interface for CernVM contextualization and deployment

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    In a virtualized environment, contextualization is the process of configuring a VM instance for the needs of various deployment use cases. Contextualization in CernVM can be done by passing a handwritten context to the user data field of cloud APIs, when running CernVM on the cloud, or by using CernVM web interface when running the VM locally. CernVM Online is a publicly accessible web interface that unifies these two procedures. A user is able to define, store and share CernVM contexts using CernVM Online and then apply them either in a cloud by using CernVM Cloud Gateway or on a local VM with the single-step pairing mechanism. CernVM Cloud Gateway is a distributed system that provides a single interface to use multiple and different clouds (by location or type, private or public). Cloud gateway has been so far integrated with OpenNebula, CloudStack and EC2 tools interfaces. A user, with access to a number of clouds, can run CernVM cloud agents that will communicate with these clouds using their interfaces, and then use one single interface to deploy and scale CernVM clusters. CernVM clusters are defined in CernVM Online and consist of a set of CernVM instances that are contextualized and can communicate with each other.Comment: Conference paper at the 2013 Computing in High Energy Physics (CHEP) Conference, Amsterda

    VELOS : a VR platform for ship-evacuation analysis

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    Virtual Environment for Life On Ships (VELOS) is a multi-user Virtual Reality (VR) system that aims to support designers to assess (early in the design process) passenger and crew activities on a ship for both normal and hectic conditions of operations and to improve ship design accordingly. This article focuses on presenting the novel features of VELOS related to both its VR and evacuation-specific functionalities. These features include: (i) capability of multiple users’ immersion and active participation in the evacuation process, (ii) real-time interactivity and capability for making on-the-fly alterations of environment events and crowd-behavior parameters, (iii) capability of agents and avatars to move continuously on decks, (iv) integrated framework for both the simplified and advanced method of analysis according to the IMO/MSC 1033 Circular, (v) enrichment of the ship geometrical model with a topological model suitable for evacuation analysis, (vi) efficient interfaces for the dynamic specification and handling of the required heterogeneous input data, and (vii) post-processing of the calculated agent trajectories for extracting useful information for the evacuation process. VELOS evacuation functionality is illustrated using three evacuation test cases for a ro–ro passenger ship

    A cognitive architecture for emergency response

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    Plan recognition, cognitive workload estimation and human assistance have been extensively studied in the AI and human factors communities, resulting in many techniques being applied to domains of various levels of realism. These techniques have seldom been integrated and evaluated as complete systems. In this paper, we report on the development of an assistant agent architecture that integrates plan recognition, current and future user information needs, workload estimation and adaptive information presentation to aid an emergency response manager in making high quality decisions under time stress, while avoiding cognitive overload. We describe the main components of a full implementation of this architecture as well as a simulation developed to evaluate the system. Our evaluation consists of simulating various possible executions of the emergency response plans used in the real world and measuring the expected time taken by an unaided human user, as well as one that receives information assistance from our system. In the experimental condition of agent assistance, we also examine the effects of different error rates in the agent's estimation of user's stat or information needs
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