362,320 research outputs found
A cookbook for temporal conceptual data modelling with description logic
We design temporal description logics suitable for reasoning about temporal conceptual data models and investigate their computational complexity. Our formalisms are based on DL-Lite logics with three types of concept inclusions (ranging from atomic concept inclusions and disjointness to the full Booleans), as well as cardinality constraints and role inclusions. In the temporal dimension, they capture future and past temporal operators on concepts, flexible and rigid roles, the operators `always' and `some time' on roles, data assertions for particular moments of time and global concept inclusions. The logics are interpreted over the Cartesian products of object domains and the flow of time (Z,<), satisfying the constant domain assumption. We prove that the most expressive of our temporal description logics (which can capture lifespan cardinalities and either qualitative or quantitative evolution constraints) turn out to be undecidable. However, by omitting some of the temporal operators on concepts/roles or by restricting the form of concept inclusions we obtain logics whose complexity ranges between PSpace and NLogSpace. These positive results were obtained by reduction to various clausal fragments of propositional temporal logic, which opens a way to employ propositional or first-order temporal provers for reasoning about temporal data models
Temporal description logic for ontology-based data access
Our aim is to investigate ontology-based data access over temporal data with validity time and ontologies capable of temporal conceptual modelling. To this end, we design a temporal description logic, TQL, that extends the standard ontology language OWL2QL, provides basic means for temporal conceptual modelling and ensures first-order rewritability of conjunctive queries for suitably defined data instances with validity time
Video semantic content analysis based on ontology
The rapid increase in the available amount of video data is creating a growing demand for efficient methods for understanding and managing it at the semantic level. New multimedia standards, such as MPEG-4 and MPEG-7, provide the basic functionalities in order to manipulate and transmit objects and metadata. But importantly, most of the content of video data at a semantic level is out of the scope of the standards. In this paper, a video semantic content analysis framework based on ontology is presented. Domain ontology is used to define high level semantic concepts and their relations in the context of the examined domain. And low-level features (e.g. visual and aural) and video content analysis algorithms are integrated into the ontology to enrich video semantic analysis. OWL is used for the ontology description. Rules in Description Logic are defined to describe how features and algorithms for video analysis should be applied according to different perception content and low-level features. Temporal Description Logic is used to describe the semantic events, and a reasoning algorithm is proposed for events detection. The proposed framework is demonstrated in a soccer video domain and shows promising results
A Generic Framework for Reasoning about Dynamic Networks of Infinite-State Processes
We propose a framework for reasoning about unbounded dynamic networks of
infinite-state processes. We propose Constrained Petri Nets (CPN) as generic
models for these networks. They can be seen as Petri nets where tokens
(representing occurrences of processes) are colored by values over some
potentially infinite data domain such as integers, reals, etc. Furthermore, we
define a logic, called CML (colored markings logic), for the description of CPN
configurations. CML is a first-order logic over tokens allowing to reason about
their locations and their colors. Both CPNs and CML are parametrized by a color
logic allowing to express constraints on the colors (data) associated with
tokens. We investigate the decidability of the satisfiability problem of CML
and its applications in the verification of CPNs. We identify a fragment of CML
for which the satisfiability problem is decidable (whenever it is the case for
the underlying color logic), and which is closed under the computations of post
and pre images for CPNs. These results can be used for several kinds of
analysis such as invariance checking, pre-post condition reasoning, and bounded
reachability analysis.Comment: 29 pages, 5 tables, 1 figure, extended version of the paper published
in the the Proceedings of TACAS 2007, LNCS 442
Notes on stochastic (bio)-logic gates: the role of allosteric cooperativity
Recent experimental breakthroughs have finally allowed to implement in-vitro
reaction kinetics (the so called {\em enzyme based logic}) which code for
two-inputs logic gates and mimic the stochastic AND (and NAND) as well as the
stochastic OR (and NOR). This accomplishment, together with the already-known
single-input gates (performing as YES and NOT), provides a logic base and paves
the way to the development of powerful biotechnological devices. The
investigation of this field would enormously benefit from a self-consistent,
predictive, theoretical framework. Here we formulate a complete statistical
mechanical description of the Monod-Wyman-Changeaux allosteric model for both
single and double ligand systems, with the purpose of exploring their practical
capabilities to express logical operators and/or perform logical operations.
Mixing statistical mechanics with logics, and quantitatively our findings with
the available biochemical data, we successfully revise the concept of
cooperativity (and anti-cooperativity) for allosteric systems, with particular
emphasis on its computational capabilities, the related ranges and scaling of
the involved parameters and its differences with classical cooperativity (and
anti-cooperativity)
PGPG: An Automatic Generator of Pipeline Design for Programmable GRAPE Systems
We have developed PGPG (Pipeline Generator for Programmable GRAPE), a
software which generates the low-level design of the pipeline processor and
communication software for FPGA-based computing engines (FBCEs). An FBCE
typically consists of one or multiple FPGA (Field-Programmable Gate Array)
chips and local memory. Here, the term "Field-Programmable" means that one can
rewrite the logic implemented to the chip after the hardware is completed, and
therefore a single FBCE can be used for calculation of various functions, for
example pipeline processors for gravity, SPH interaction, or image processing.
The main problem with FBCEs is that the user need to develop the detailed
hardware design for the processor to be implemented to FPGA chips. In addition,
she or he has to write the control logic for the processor, communication and
data conversion library on the host processor, and application program which
uses the developed processor. These require detailed knowledge of hardware
design, a hardware description language such as VHDL, the operating system and
the application, and amount of human work is huge. A relatively simple design
would require 1 person-year or more. The PGPG software generates all necessary
design descriptions, except for the application software itself, from a
high-level design description of the pipeline processor in the PGPG language.
The PGPG language is a simple language, specialized to the description of
pipeline processors. Thus, the design of pipeline processor in PGPG language is
much easier than the traditional design. For real applications such as the
pipeline for gravitational interaction, the pipeline processor generated by
PGPG achieved the performance similar to that of hand-written code. In this
paper we present a detailed description of PGPG version 1.0.Comment: 24 pages, 6 figures, accepted PASJ 2005 July 2
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