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Record W2138875386 · doi:10.1109/wimob.2007.4390864

Managing and Deployment of Applications with OSGi in the Context of Smart Home

2007· article· en· W2138875386 on OpenAlexaff
Robert J. Vallerand, Sylvain Giroux

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSoftware deploymentComputer scienceContext (archaeology)Ubiquitous computingSmart environmentResource (disambiguation)Home automationEmbedded systemSoftware engineeringInternet of ThingsHuman–computer interactionOperating systemComputer network

Abstract

fetched live from OpenAlex

The presence of a multitude of heterogeneous devices in a smart home environment create a whole puzzle when comes the time to deploy, update, or manage applications on these devices. The configuration and the updating of applications in that context can be expensive, as well as resource and time consuming, especially when there are several similar environments to implement. This paper considers those problems, brings a glimpse on possible solutions, and proposes the use of the OSGi framework to ease the deployment and the management of applications. Moreover this paper presents a summary of a distributed system currently in last phase of development that will resolve the proposed problematic. This system allows the remote managing and deployment in the context of a distributed and pervasive environment for cognitively impaired people.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.135

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.248
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2007
Admission routes1
Has abstractyes

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