28,016 research outputs found
Business Process Retrieval Based on Behavioral Semantics
This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called "BeMantics" for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The "BeMantics" framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics propertie
Ontology-based collaborative framework for disaster recovery scenarios
This paper aims at designing of adaptive framework for supporting
collaborative work of different actors in public safety and disaster recovery
missions. In such scenarios, firemen and robots interact to each other to reach
a common goal; firemen team is equipped with smart devices and robots team is
supplied with communication technologies, and should carry on specific tasks.
Here, reliable connection is mandatory to ensure the interaction between
actors. But wireless access network and communication resources are vulnerable
in the event of a sudden unexpected change in the environment. Also, the
continuous change in the mission requirements such as inclusion/exclusion of
new actor, changing the actor's priority and the limitations of smart devices
need to be monitored. To perform dynamically in such case, the presented
framework is based on a generic multi-level modeling approach that ensures
adaptation handled by semantic modeling. Automated self-configuration is driven
by rule-based reconfiguration policies through ontology
Online Tensor Methods for Learning Latent Variable Models
We introduce an online tensor decomposition based approach for two latent
variable modeling problems namely, (1) community detection, in which we learn
the latent communities that the social actors in social networks belong to, and
(2) topic modeling, in which we infer hidden topics of text articles. We
consider decomposition of moment tensors using stochastic gradient descent. We
conduct optimization of multilinear operations in SGD and avoid directly
forming the tensors, to save computational and storage costs. We present
optimized algorithm in two platforms. Our GPU-based implementation exploits the
parallelism of SIMD architectures to allow for maximum speed-up by a careful
optimization of storage and data transfer, whereas our CPU-based implementation
uses efficient sparse matrix computations and is suitable for large sparse
datasets. For the community detection problem, we demonstrate accuracy and
computational efficiency on Facebook, Yelp and DBLP datasets, and for the topic
modeling problem, we also demonstrate good performance on the New York Times
dataset. We compare our results to the state-of-the-art algorithms such as the
variational method, and report a gain of accuracy and a gain of several orders
of magnitude in the execution time.Comment: JMLR 201
FAST : a fault detection and identification software tool
The aim of this work is to improve the reliability and safety of complex critical control systems by contributing to the systematic application of fault diagnosis. In order to ease the utilization of fault detection and isolation (FDI) tools in the industry, a systematic approach is required to allow the process engineers to analyze a system from this perspective. In this way, it should be possible to analyze this system to find if it provides the required fault diagnosis and redundancy according to the process criticality. In addition, it should be possible to evaluate what-if scenarios by slightly modifying the process (f.i. adding sensors or changing their placement) and evaluating the impact in terms of the fault diagnosis and redundancy possibilities.
Hence, this work proposes an approach to analyze a process from the FDI perspective and for this purpose provides the tool FAST which covers from the analysis and design phase until the final FDI supervisor implementation in a real process. To synthesize the process information, a very simple format has been defined based on XML. This format provides the needed information to systematically perform the Structural Analysis of that process. Any process can be analyzed, the only restriction is that the models of the process components need to be available in the FAST tool. The processes are described in FAST in terms of process variables, components and relations and the tool performs the structural analysis of the process obtaining: (i) the structural matrix, (ii) the perfect matching, (iii) the analytical redundancy relations (if any) and (iv) the fault signature matrix.
To aid in the analysis process, FAST can operate stand alone in simulation mode allowing the process engineer to evaluate the faults, its detectability and implement changes in the process components and topology to improve the diagnosis and redundancy capabilities. On the other hand, FAST can operate on-line connected to the process plant through an OPC interface. The OPC interface enables the possibility to connect to almost any process which features a SCADA system for supervisory control. When running in on-line mode, the process is monitored by a software agent known as the Supervisor Agent.
FAST has also the capability of implementing distributed FDI using its multi-agent architecture. The tool is able to partition complex industrial processes into subsystems, identify which process variables need to be shared by each subsystem and instantiate a Supervision Agent for each of the partitioned subsystems. The Supervision Agents once instantiated will start diagnosing their local components and handle the requests to provide the variable values which FAST has identified as shared with other agents to support the distributed FDI process.Per tal de facilitar la utilitzaciĂł d'eines per la detecciĂł i identificaciĂł de fallades (FDI) en la indĂşstria, es requereix un enfocament sistemĂ tic per permetre als enginyers de processos analitzar un sistema des d'aquesta perspectiva. D'aquesta forma, hauria de ser possible analitzar aquest sistema per determinar si proporciona el diagnosi de fallades i la redundĂ ncia d'acord amb la seva criticitat. A mĂ©s, hauria de ser possible avaluar escenaris de casos modificant lleugerament el procĂ©s (per exemple afegint sensors o canviant la seva localitzaciĂł) i avaluant l'impacte en quant a les possibilitats de diagnosi de fallades i redundĂ ncia. Per tant, aquest projecte proposa un enfocament per analitzar un procĂ©s des de la perspectiva FDI i per tal d'implementar-ho proporciona l'eina FAST la qual cobreix des de la fase d'anĂ lisi i disseny fins a la implementaciĂł final d'un supervisor FDI en un procĂ©s real. Per sintetitzar la informaciĂł del procĂ©s s'ha definit un format simple basat en XML. Aquest format proporciona la informaciĂł necessĂ ria per realitzar de forma sistemĂ tica l'AnĂ lisi Estructural del procĂ©s. Qualsevol procĂ©s pot ser analitzat, nomĂ©s hi ha la restricciĂł de que els models dels components han d'estar disponibles en l'eina FAST. Els processos es descriuen en termes de variables de procĂ©s, components i relacions i l'eina realitza l'anĂ lisi estructural obtenint: (i) la matriu estructural, (ii) el Perfect Matching, (iii) les relacions de redundĂ ncia analĂtica, si n'hi ha, i (iv) la matriu signatura de fallades. Per ajudar durant el procĂ©s d'anĂ lisi, FAST pot operar aĂŻlladament en mode de simulaciĂł permetent a l'enginyer de procĂ©s avaluar fallades, la seva detectabilitat i implementar canvis en els components del procĂ©s i la topologia per tal de millorar les capacitats de diagnosi i redundĂ ncia. Per altra banda, FAST pot operar en lĂnia connectat al procĂ©s de la planta per mitjĂ d'una interfĂcie OPC. La interfĂcie OPC permet la possibilitat de connectar gairebĂ© a qualsevol procĂ©s que inclogui un sistema SCADA per la seva supervisiĂł. Quan funciona en mode en lĂnia, el procĂ©s estĂ monitoritzat per un agent software anomenat l'Agent Supervisor. Addicionalment, FAST tĂ© la capacitat d'implementar FDI de forma distribuĂŻda utilitzant la seva arquitectura multi-agent. L'eina permet dividir sistemes industrials complexes en subsistemes, identificar quines variables de procĂ©s han de ser compartides per cada subsistema i generar una instĂ ncia d'Agent Supervisor per cadascun dels subsistemes identificats. Els Agents Supervisor un cop activats, començaran diagnosticant els components locals i despatxant les peticions de valors per les variables que FAST ha identificat com compartides amb altres agents, per tal d'implementar el procĂ©s FDI de forma distribuĂŻda.Postprint (published version
Abstracting object interactions using composition filters
It is generally claimed that object-based models are very suitable for building distributed system architectures since object interactions follow the client-server model. To cope with the complexity of today's distributed systems, however, we think that high-level linguistic mechanisms are needed to effectively structure, abstract and reuse object interactions. For example, the conventional object-oriented model does not provide high-level language mechanisms to model layered system architectures. Moreover, we consider the message passing model of the conventional object-oriented model as being too low-level because it can only specify object interactions that involve two partner objects at a time and its semantics cannot be extended easily. This paper introduces Abstract Communication Types (ACTs), which are objects that abstract interactions among objects. ACTs make it easier to model layered communication architectures, to enforce the invariant behavior among objects, to reduce the complexity of programs by hiding the interaction details in separate modules and to improve reusability through the application of object-oriented principles to ACT classes. We illustrate the concept of ACTs using the composition filters model
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