Search results for "Data model"

Acquisition, filtering and toll data processing system for obtaining origin-destination matrix and travel times on highways

2012

This paper presents an acquisition, filtering and real-time toll data processing system that provides a base for resolution and generation of studies and models of behavior on highways. Crossing points estimation, speed calculation, study traffic flow, travel time estimation and stopping points can also be provided. The complexity of processing with supplied data volume makes indispensable a less relevant information filtering. This filtering can be done through indicators such as speed or nullity of fields and a performance improvement job in database level using views, materializations, partitioning and parallelism. A web application called MODA has been developed. This application make e…

Applying a Data Quality Model to Experiments in Software Engineering

2014

Data collection and analysis are key artifacts in any software engineering experiment. However, these data might contain errors. We propose a Data Quality model specific to data obtained from software engineering experiments, which provides a framework for analyzing and improving these data. We apply the model to two controlled experiments, which results in the discovery of data quality problems that need to be addressed. We conclude that data quality issues have to be considered before obtaining the experimental results.

ISIS: a semantic mediation model and an agent based architecture for GIS interoperability

2003

The diversity of spatial information systems promotes the need to integrate heterogeneous spatial or geographic information systems (GIS) in a cooperative environment. The paper describes the research project ISIS (Interoperable Spatial Information System) which is a semantic mediation approach to support GIS interoperability. Its key characteristic is a dynamic resolution of semantic conflicts which is adequate for achieving autonomy, flexibility and extensibility. We propose a spatial OO data model and a mediation architecture based on multi-agent paradigm to support GIS interoperability.

Spatio-temporal Schema Integration with Validation: A Practical Approach

2005

We propose to enhance a schema integration process with a validation phase employing logic-based data models. In our methodology, we validate the source schemas against the data model; the inter-schema mappings are validated against the semantics of the data model and the syntax of the correspondence language. In this paper, we focus on how to employ a reasoning engine to validate spatio-temporal schemas and describe where the reasoning engine is plugged into our integration methodology. The validation phase distinguishes our integration methodology from other approaches. We shift the emphasis on automation from the a priori discovery to the a posteriori checking of the inter-schema mapping…

The Model of Possible Web Data Retrieval

2015

In the Dempster-Shafer's theory of evidence, for incorporating uncertainty, the valuation assigns to the data tables the degrees of belief for these data. Firstly, we are looking for the answers to the following questions. Is there a valuation-based system in which combination and marginalization operate on valuations? Has this system prosperities analogical to the t-norm system? In the t-norm system of the valuation for the specific database attributes configuration can be described the algebra of possible data set in which can be interpreted the Information Retrieval Logic.

Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data

2018

Density estimation of streaming data is a relevant task in numerous domains. In this paper, a novel non-parametric density estimator called FRONT (forest of normalized trees) is introduced. It uses a structure of multiple normalized trees, segments the feature space of the data stream through a periodically updated linear transformation and is able to adapt to ever evolving data streams. FRONT provides accurate density estimation and performs favorably compared to existing online density estimators in terms of the average log score on multiple standard data sets. Its low complexity, linear runtime as well as constant memory usage, makes FRONT by design suitable for large data streams. Final…

LC3: A spatio-temporal and semantic model for knowledge discovery from geospatial datasets

2015

International audience; There is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a mo…

Delay-oriented data traffic migration in maritime mobile communication environments

2012

Maritime ship-to-shore communication has to satisfy different user requirements while suffering dynamic communication circumstances. Satellite networks are the primary means to communicate between ship and shore. The idea of compensating the deficiency of satellite communication with other terrestrial networks is not new. However, focus was often on how to keep users always best connected, without considering respective application needs or the potential disconnections. In this paper, we propose a delay-oriented satellite data traffic migration solution, exploiting the route repetitiveness and predictability of ships, leveraging the delay tolerance of many communication applications, with t…

Conceptual and Paradigmatic Foundations of ISD

1995

Latent force models for earth observation time series prediction

2016

We introduce latent force models for Earth observation time series analysis. The model uses Gaussian processes and differential equations to combine data driven modelling with a physical model of the system. The LFM presented here performs multi-output structured regression, adapts to the signal characteristics, it can cope with missing data in the time series, and provides explicit latent functions that allow system analysis and evaluation. We successfully illustrate the performance in challenging scenarios of crop monitoring from space, providing time-resolved time series predictions.