2,609 research outputs found
Semantic Support for Log Analysis of Safety-Critical Embedded Systems
Testing is a relevant activity for the development life-cycle of Safety
Critical Embedded systems. In particular, much effort is spent for analysis and
classification of test logs from SCADA subsystems, especially when failures
occur. The human expertise is needful to understand the reasons of failures,
for tracing back the errors, as well as to understand which requirements are
affected by errors and which ones will be affected by eventual changes in the
system design. Semantic techniques and full text search are used to support
human experts for the analysis and classification of test logs, in order to
speedup and improve the diagnosis phase. Moreover, retrieval of tests and
requirements, which can be related to the current failure, is supported in
order to allow the discovery of available alternatives and solutions for a
better and faster investigation of the problem.Comment: EDCC-2014, BIG4CIP-2014, Embedded systems, testing, semantic
discovery, ontology, big dat
A review of key planning and scheduling in the rail industry in Europe and UK
Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR
Km4City Ontology Building vs Data Harvesting and Cleaning for Smart-city Services
Presently, a very large number of public and private data sets are available
from local governments. In most cases, they are not semantically interoperable
and a huge human effort would be needed to create integrated ontologies and
knowledge base for smart city. Smart City ontology is not yet standardized, and
a lot of research work is needed to identify models that can easily support the
data reconciliation, the management of the complexity, to allow the data
reasoning. In this paper, a system for data ingestion and reconciliation of
smart cities related aspects as road graph, services available on the roads,
traffic sensors etc., is proposed. The system allows managing a big data volume
of data coming from a variety of sources considering both static and dynamic
data. These data are mapped to a smart-city ontology, called KM4City (Knowledge
Model for City), and stored into an RDF-Store where they are available for
applications via SPARQL queries to provide new services to the users via
specific applications of public administration and enterprises. The paper
presents the process adopted to produce the ontology and the big data
architecture for the knowledge base feeding on the basis of open and private
data, and the mechanisms adopted for the data verification, reconciliation and
validation. Some examples about the possible usage of the coherent big data
knowledge base produced are also offered and are accessible from the RDF-Store
and related services. The article also presented the work performed about
reconciliation algorithms and their comparative assessment and selection
Developing a distributed electronic health-record store for India
The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
Towards Model Checking Executable UML Specifications in mCRL2
We describe a translation of a subset of executable UML (xUML) into the process algebraic specification language mCRL2. This subset includes class diagrams with class generalisations, and state machines with signal and change events. The choice of these xUML constructs is dictated by their use in the modelling of railway interlocking systems. The long-term goal is to verify safety properties of interlockings modelled in xUML using the mCRL2 and LTSmin toolsets. Initial verification of an interlocking toy example demonstrates that the safety properties of model instances depend crucially on the run-to-completion assumptions
Dependability checking with StoCharts: Is train radio reliable enough for trains?
Performance, dependability and quality of service (QoS) are prime aspects of the UML modelling domain. To capture these aspects effectively in the design phase, we have recently proposed STOCHARTS, a conservative extension of UML statechart diagrams. In this paper, we apply the STOCHART formalism to a safety critical design problem. We model a part of the European Train Control System specification, focusing on the risks of wireless communication failures in future high-speed cross-European trains. Stochastic model checking with the model checker PROVER enables us to derive constraints under which the central quality requirements are satisfied by the STOCHART model. The paper illustrates the flexibility and maturity of STOCHARTS to model real problems in safety critical system design
A comparative reliability analysis of ETCS train radio communications
StoCharts have been proposed as a UML statechart extension for performance and dependability evaluation, and were applied in the context of train radio reliability assessment to show the principal tractability of realistic cases with this approach. In this paper, we extend on this bare feasibility result in two important directions. First, we sketch the cornerstones of a mechanizable translation of StoCharts to MoDeST. The latter is a process algebra-based formalism supported by the Motor/Mƶbius tool tandem. Second, we exploit this translation for a detailed analysis of the train radio case study
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