33,551 research outputs found
Decision Support Tools for Cloud Migration in the Enterprise
This paper describes two tools that aim to support decision making during the
migration of IT systems to the cloud. The first is a modeling tool that
produces cost estimates of using public IaaS clouds. The tool enables IT
architects to model their applications, data and infrastructure requirements in
addition to their computational resource usage patterns. The tool can be used
to compare the cost of different cloud providers, deployment options and usage
scenarios. The second tool is a spreadsheet that outlines the benefits and
risks of using IaaS clouds from an enterprise perspective; this tool provides a
starting point for risk assessment. Two case studies were used to evaluate the
tools. The tools were useful as they informed decision makers about the costs,
benefits and risks of using the cloud.Comment: To appear in IEEE CLOUD 201
Public HMDs: Modeling and Understanding User Behavior Around Public Head-Mounted Displays
Head-Mounted Displays (HMDs) are becoming ubiquitous; we are starting to see them deployed in public for different purposes. Museums, car companies and travel agencies use HMDs to promote their products. As a result, situations arise where users use them in public without experts supervision. This leads to challenges and opportunities, many of which are experienced in public display installations. For example, similar to public displays, public HMDs struggle to attract the passer-by's attention, but benefit from the honeypot effect that draws attention to them. Also passersby might be hesitant to wear a public HMD, due to the fear that its owner might not approve, or due to the perceived need for a prior permission. In this work, we discuss how public HMDs can benefit from research in public displays. In particular, based on the results of an in-the-wild deployment of a public HMD, we propose an adaptation of the audience funnel flow model of public display users to fit the context of public HMD usage. We discuss how public HMDs bring in challenges and opportunities, and create novel research directions that are relevant to both researchers in HMDs and researchers in public displays
A Review of the Enviro-Net Project
Ecosystems monitoring is essential to properly understand their development
and the effects of events, both climatological and anthropological in nature.
The amount of data used in these assessments is increasing at very high rates.
This is due to increasing availability of sensing systems and the development
of new techniques to analyze sensor data. The Enviro-Net Project encompasses
several of such sensor system deployments across five countries in the
Americas. These deployments use a few different ground-based sensor systems,
installed at different heights monitoring the conditions in tropical dry
forests over long periods of time. This paper presents our experience in
deploying and maintaining these systems, retrieving and pre-processing the
data, and describes the Web portal developed to help with data management,
visualization and analysis.Comment: v2: 29 pages, 5 figures, reflects changes addressing reviewers'
comments v1: 38 pages, 8 figure
An In Depth Study into Using EMI Signatures for Appliance Identification
Energy conservation is a key factor towards long term energy sustainability.
Real-time end user energy feedback, using disaggregated electric load
composition, can play a pivotal role in motivating consumers towards energy
conservation. Recent works have explored using high frequency conducted
electromagnetic interference (EMI) on power lines as a single point sensing
parameter for monitoring common home appliances. However, key questions
regarding the reliability and feasibility of using EMI signatures for
non-intrusive load monitoring over multiple appliances across different sensing
paradigms remain unanswered. This work presents some of the key challenges
towards using EMI as a unique and time invariant feature for load
disaggregation. In-depth empirical evaluations of a large number of appliances
in different sensing configurations are carried out, in both laboratory and
real world settings. Insights into the effects of external parameters such as
line impedance, background noise and appliance coupling on the EMI behavior of
an appliance are realized through simulations and measurements. A generic
approach for simulating the EMI behavior of an appliance that can then be used
to do a detailed analysis of real world phenomenology is presented. The
simulation approach is validated with EMI data from a router. Our EMI dataset -
High Frequency EMI Dataset (HFED) is also released
Persuasive system design does matter: a systematic review of adherence to web-based interventions
Background: Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence.
Objective: This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention.
Methods: We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence.
Results: We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence.
Conclusions: Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adher
- …