A Functional Data Model Approach to Querying RDF/RDFS Data

A stream validation system called SVALI is developed in order to continuously validate correct behavior of industrial equipment. A functional data model allows the user to define meta-data, analyses, and queries about the monitored equipment in terms of types and functions. Two different approaches to validate that sensor readings in a data stream indicate correct equipment behavior are supported: with the model-and-validate approach anomalies are detected based on a physical model, while with learn-and-validate anomalies are detected by comparing streaming data with a model of normal behavior learnt during a training period. Both models are expressed on a high level using the functional data model and query language. The experiments show that parallel stream processing enables SVALI to scale very well with respect to system throughput and response time. The paper is based on a real world application for wheel loader slippage detection at Volvo Construction Equipment implemented in SVALI.

In this paper we describe the design and implementation of a high-level query language FQUERY which applies the concepts of the functional data model to the retrieval of information from relational databases created on a small PDP-11 system by the RISS relational system described in [Me]. We describe the query language and the functional data model and discuss the benefits they provide for the casual user in expressing queries in a conceptually natural manner.

We present in this paper Gql, a declarative graphical query language based on the functional data model. Gql queries are fully represented by a single diagram. Without containing any explicit boolean operators or logical quantifiers, Gql provides users of varying degrees of programming experience, with the same expressive power for retrieval as SQL. The design philosophy and characteristics of the language are discussed, and an informal presentation of Gql's constructs and semantics is given. Finally, gql_int, the implementation of an interface for the language, is described.

Many countries have implemented social programs providing long-term financial or in-kind entitlements. These programs often focus on specific age-groups and consequently their expenditure streams are subject to demographic change. Given the strains already existing on public budgets, long-term forecasts are an increasingly important instrument to monitor the budgetary consequences of social programs. The expected development of the labour force is a key input to these forecasts. We Produce forecasts of age-specific labour market participation rates, combining a functional data approach with information on education, marital status and other exogenous variables.

The last couple of years have shown an increased demand for database management systems for CAD/CAM applications. One such application, that we investigate in this paper is computer geometry. In this paper we first provide a brief introduction to geometric modelling from a database perspective. The functional data model with its database language DAPLEX is analyzed as a candidate for supporting computer geometry applications. It is argued that the functional model adequately supports the structural object orientation of geometrical applications but not the behavioral object orientation. Aside from structural representation of (engineering) objects one also needs the facility to integrate even computationally complex application-specific operations to manipulate the objects in the data model. Therefore, in EDAPLEX we propose some extensions to DAPLEX that consist of operations, control structures, and virtual functions. A prototype implementation of EDAPLEX has been carried out as a front end to the relational database system INGRES to benchmark EDAPLEX for two particular application areas: the boundary representation and the constructive solid geometry representation of solid objects.

We discuss the important database theme of Data Independence and how object oriented database applications are failing to perceive its benefits, and instead put too much reliance on encapsulation. The P/FDM object-oriented database is based on the functional data model and has a modular design based on data independence, which allows alternative kinds of object storage to be used. In this work, a relational database management system has been used to provide object storage, and we describe how the data access routines have been implemented. The principal query language used with P/FDM is Daplex, which is normally translated to Prolog, including calls to the basic data access routines. The query is optimised to minimise the expected number of calls. This gives very general method execution and pattern matching search. However, much better performance can be achieved for simpler data-intensive Daplex queries against a relational storage module by translating these to a single SQL statement, which is possible because of data independence.

Syntax and Semantics of Gql, a Graphical Query Language

This paper discusses the advantages of a functional approach to data modelling. This approach forms the basis for DAPLEX, a high-level language for data description and manipulation. We describe the DAPLEX language and the functional data model and examine the benefits they provide as tools for expressing and solving problems in database management.

ABSTRACTThe aim of this article is to develop a novel class of functional structural equation models (FSEMs) for dissecting functional genetic and environmental effects on twin functional data, while characterizing the varying association between functional data and covariates of interest. We propose a three-stage estimation procedure to estimate varying coefficient functions for various covariates (e.g., gender) as well as three covariance operators for the genetic and environmental effects. We develop an inference procedure based on weighted likelihood ratio statistics to test the genetic/environmental effect at either a fixed location or a compact region. We also systematically carry out the theoretical analysis of the estimated varying functions, the weighted likelihood ratio statistics, and the estimated covariance operators. We conduct extensive Monte Carlo simulations to examine the finite-sample performance of the estimation and inference procedures. We apply the proposed FSEM to quantify the degree of genetic and environmental effects on twin white matter tracts obtained from the UNC early brain development study. Supplementary materials for this article are available online.

Modeling Price Dynamics in eBay Auctions Using Principal Differential Analysis

Dataflow is a method for parallel computation in which the elementary operations of the computer are activated by the flow of data. Computation is carried out in some autonomous processors which are connected to each other by some communication lines. The author shows how this model of computation can lead to interesting ideas in the management of knowledge bases. Each of the processors in the system is seen as a database machine which makes use of the modern sophisticated storage devices. Thus parallelism is gained both at the storage level (as is customary in database literature) and in the overall computation process. >

Context-aware and live multimedia content production and delivery can be considered as key issues for enabling dynamic sharing among members of living social networks. The proposed cross-platform environment, deployed on J2ME technology, enables mobile users with a suitable tool for content production, dynamic context and metadata integration and content publication directly from smart devices. Multimedia content is provided with an extensible semantic and functional data model that makes shared content easily to be catalogued, classified and managed within large scale communities. Moreover, an advanced context management model provides users with multiple options for effective content publication. Support for live streaming and potential interaction with multiple social communities makes the platform really flexible within different domains and application fields.

Granular computing (GrC) is an emerging discipline of information theory that strives to allow reasoning and analysis based on varying levels of information granularity (from fine to coarse). In GrC, the entire information universe can be organised based on many different criteria, allowing the information to be abstracted, aggregated, classified, generalised and so on, based on various characteristics (e.g., data similarity, operational usage, etc.). As a result, GrC relies on information models to describe the universe, the elements of the universe and the composition of each element. In this paper, candidate information models for GrC are explored and assessed, including: the attribute-based data model, the relational data model, the functional data model and the extensible markup language. This includes a description of these models in terms of their concepts, data definition and data manipulation and an analysis of the suitability in support of GrC.

On-line Fault Diagnosis by Combining Functional and Dynamic Modelling of Chemical Plants

Surface functional models