94,487 research outputs found
Metadata and ontologies for organizing students’ memories and learning: standards and convergence models for context awareness
Este artÃculo trata de las ontologÃas que sirven para la comprensión en contexto y la Gestión de la Información Personal (PIM)y su aplicabilidad al proyecto Memex Metadata(M2). M2 es un proyecto de investigación de la Universidad de Carolina del Norte en Chapel Hill para mejorar la memoria digital de los alumnos utilizando tablet PC, la tecnologÃa SenseCam de Microsoft y otras tecnologÃas móviles(p.ej. un dispositivo de GPS) para capturar el contexto del aprendizaje. Este artÃculo presenta el proyecto M2, dicute el concepto de los portafolios digitales en las actuales tendencias educativas, relacionándolos con las tecnologÃas emergentes, revisa las ontologÃas relevantes y su relación con el proyecto CAF (Context Awareness Framework), y concluye identificando las lÃneas de investigación futuras.This paper focuses on ontologies supporting context awareness and Personal Information Management (PIM) and their
applicability in Memex Metadata (M2) project. M2 is a research project of the University of North Carolina at Chapel Hill to
improve student digital memories using the tablet PC, Microsoft’s SenseCam technology, and other mobile technologies (e.g.,
a GPS device) to capture context. The M2 project offers new opportunities studying students’ learning with digital
technologies. This paper introduces the M2 project; discusses E-portfolios and current educational trends related to pervasive
computing; reviews relevant ontologies and their relationship to the projects’ CAF (context awareness framework), and
concludes by identifying future research directions
Federated Embedded Systems – a review of the literature in related fields
This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous
computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways
Evaluating Content-centric vs User-centric Ad Affect Recognition
Despite the fact that advertisements (ads) often include strongly emotional
content, very little work has been devoted to affect recognition (AR) from ads.
This work explicitly compares content-centric and user-centric ad AR
methodologies, and evaluates the impact of enhanced AR on computational
advertising via a user study. Specifically, we (1) compile an affective ad
dataset capable of evoking coherent emotions across users; (2) explore the
efficacy of content-centric convolutional neural network (CNN) features for
encoding emotions, and show that CNN features outperform low-level emotion
descriptors; (3) examine user-centered ad AR by analyzing Electroencephalogram
(EEG) responses acquired from eleven viewers, and find that EEG signals encode
emotional information better than content descriptors; (4) investigate the
relationship between objective AR and subjective viewer experience while
watching an ad-embedded online video stream based on a study involving 12
users. To our knowledge, this is the first work to (a) expressly compare user
vs content-centered AR for ads, and (b) study the relationship between modeling
of ad emotions and its impact on a real-life advertising application.Comment: Accepted at the ACM International Conference on Multimodal Interation
(ICMI) 201
The Role of Ethological Observation for Measuring Animal Reactions to Biotelemetry Devices
This paper presents a methodological approach used to assess the wearability of biotelemetry devices in animals. A detailed protocol to gather quantitative and qualitative ethological observations was adapted and tested in an experimental study of 13 cat participants wearing two different GPS devices. The aim was twofold: firstly, to ascertain the potential interference generated by the devices on the animal body and behavior by quantifying and characterizing it; secondly, to individuate device features potentially responsible for the influence registered, and establish design requirements. This research contributes towards the development of a framework for evaluating the design of wearer-centered biotelemetry interventions for animals, consistent with values advocated by Animal- Computer Interaction researchers
Dynamics of Affordances and Implications for Design
Affordance is an important concept in HCI. There are various interpretations of affordances but it has been difficult to use this concept for design purposes. Often the treatment of affordances in the current HCI literature has been as a one-to-one relationship between a user and an artefact. According to our views, affordance is a dynamic, always emerging relationship between a human and his environment. We believe that the social and cultural contexts within which an artefact is situated affect the way in which the artefact is used. Using a Structuration Theory approach, we argue that affordances need also be treated at a much broader level, encompassing social and cultural aspects. We suggest that affordances should be seen at three levels: single user, organizational (or work group) and societal. Focusing on the organizational level affordances, we provide details of several important factors that affect the emergence of affordances
Affect Recognition in Ads with Application to Computational Advertising
Advertisements (ads) often include strongly emotional content to leave a
lasting impression on the viewer. This work (i) compiles an affective ad
dataset capable of evoking coherent emotions across users, as determined from
the affective opinions of five experts and 14 annotators; (ii) explores the
efficacy of convolutional neural network (CNN) features for encoding emotions,
and observes that CNN features outperform low-level audio-visual emotion
descriptors upon extensive experimentation; and (iii) demonstrates how enhanced
affect prediction facilitates computational advertising, and leads to better
viewing experience while watching an online video stream embedded with ads
based on a study involving 17 users. We model ad emotions based on subjective
human opinions as well as objective multimodal features, and show how
effectively modeling ad emotions can positively impact a real-life application.Comment: Accepted at the ACM International Conference on Multimedia (ACM MM)
201
Activity-Centric Computing Systems
• Activity-Centric Computing (ACC) addresses deep-rooted information management problems in traditional application centric computing by providing a unifying computational model for human goal-oriented ‘activity,’ cutting across system boundaries. • We provide a historical review of the motivation for and development of ACC systems, and highlight the need for broadening up this research topic to also include low-level system research and development. • ACC concepts and technology relate to many facets of computing; they are relevant for researchers working on new computing models and operating systems, as well as for application designers seeking to incorporate these technologies in domain-specific applications
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