Affordances and Safe Design of Assistance Wearable Virtual Environment of Gesture

Safety and reliability are the main issues for designing assistance wearable virtual environment of technical gesture in aerospace, or health application domains. That needs the integration in the same isomorphic engineering framework of human requirements, systems requirements and the rationale of their relation to the natural and artifactual environment.To explore coupling integration and design functional organization of support technical gesture systems, firstly ecological psychologyprovides usa heuristicconcept: the affordance. On the other hand mathematical theory of integrative physiology provides us scientific concepts: the stabilizing auto-association principle and functional interaction.After demonstrating the epistemological consistence of these concepts, we define an isomorphic framework to describe and model human systems integration dedicated to human in-the-loop system engineering.We present an experimental approach of safe design of assistance wearable virtual environment of gesture based in laboratory and parabolic flights. On the results, we discuss the relevance of our conceptual approach and the applications to future assistance of gesture wearable systems engineering

A Comparison of Visualisation Methods for Disambiguating Verbal Requests in Human-Robot Interaction

Picking up objects requested by a human user is a common task in human-robot interaction. When multiple objects match the user's verbal description, the robot needs to clarify which object the user is referring to before executing the action. Previous research has focused on perceiving user's multimodal behaviour to complement verbal commands or minimising the number of follow up questions to reduce task time. In this paper, we propose a system for reference disambiguation based on visualisation and compare three methods to disambiguate natural language instructions. In a controlled experiment with a YuMi robot, we investigated real-time augmentations of the workspace in three conditions -- mixed reality, augmented reality, and a monitor as the baseline -- using objective measures such as time and accuracy, and subjective measures like engagement, immersion, and display interference. Significant differences were found in accuracy and engagement between the conditions, but no differences were found in task time. Despite the higher error rates in the mixed reality condition, participants found that modality more engaging than the other two, but overall showed preference for the augmented reality condition over the monitor and mixed reality conditions

Performance Evaluation of Distributed Computing Environments with Hadoop and Spark Frameworks

Recently, due to rapid development of information and communication technologies, the data are created and consumed in the avalanche way. Distributed computing create preconditions for analyzing and processing such Big Data by distributing the computations among a number of compute nodes. In this work, performance of distributed computing environments on the basis of Hadoop and Spark frameworks is estimated for real and virtual versions of clusters. As a test task, we chose the classic use case of word counting in texts of various sizes. It was found that the running times grow very fast with the dataset size and faster than a power function even. As to the real and virtual versions of cluster implementations, this tendency is the similar for both Hadoop and Spark frameworks. Moreover, speedup values decrease significantly with the growth of dataset size, especially for virtual version of cluster configuration. The problem of growing data generated by IoT and multimodal (visual, sound, tactile, neuro and brain-computing, muscle and eye tracking, etc.) interaction channels is presented. In the context of this problem, the current observations as to the running times and speedup on Hadoop and Spark frameworks in real and virtual cluster configurations can be very useful for the proper scaling-up and efficient job management, especially for machine learning and Deep Learning applications, where Big Data are widely present.Comment: 5 pages, 1 table, 2017 IEEE International Young Scientists Forum on Applied Physics and Engineering (YSF-2017) (Lviv, Ukraine

Mixed reality participants in smart meeting rooms and smart home enviroments

Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments

Multimodal fusion : gesture and speech input in augmented reality environment

Augmented Reality (AR) has the capability to interact with the virtual objects and physical objects simultaneously since it combines the real world with virtual world seamlessly. However, most AR interface applies conventional Virtual Reality (VR) interaction techniques without modification. In this paper we explore the multimodal fusion for AR with speech and hand gesture input. Multimodal fusion enables users to interact with computers through various input modalities like speech, gesture, and eye gaze. At the first stage to propose the multimodal interaction, the input modalities are decided to be selected before be integrated in an interface. The paper presents several related works about to recap the multimodal approaches until it recently has been one of the research trends in AR. It presents the assorted existing works in multimodal for VR and AR. In AR, multimodal considers as the solution to improve the interaction between the virtual and physical entities. It is an ideal interaction technique for AR applications since AR supports interactions in real and virtual worlds in the real-time. This paper describes the recent studies in AR developments that appeal gesture and speech inputs. It looks into multimodal fusion and its developments, followed by the conclusion.This paper will give a guideline on multimodal fusion on how to integrate the gesture and speech inputs in AR environment