Conceptual Workflow for Complex Data Integration using AXML

International audienceRelevant data for decision support systems are available everywhere and in various formats. Such data must be integrated into a unified format. Traditional data integration approaches are not adapted to handle complex data. Thus, we exploit the Active XML language for integrating complex data. Its XML part allows to unify, model and store complex data. Moreover, its services part tackles the distributed issue of data sources. Accordingly, different integration tasks are proposed as services. These services are managed via a set of active rules that are built upon metadata and events of the integration system. In this paper, we design an architecture for integrating complex data autonomously. We have also designed the workflow for data integration tasks

UNICOMP: Identification of Enterprise Competencies to Build Collaborative Networks

Abstract. In a context of decision-aid to support the identification of collaborative networks, this paper focuses on extracting essential facets of firm competencies. Due to the complexity of the notion of competence, this contribution is based on a semantic representation of information using semantic ontology, bonds and a linguistic treatment based on the utilization of syntactic patterns. To identify enterprise competencies, the UNICOMP system uses company web sites as information source, as well as a general ontology of competencies as semantic resource

TECHNIQUE OF CONTROL PMSM POWERED BY PV PANEL USING PREDICTIVE CONTROLLER OF DTC-SVM

The present paper is a part of the study of Direct Torque Control based (DTC) on space vector modulation using predictive controller (Predictive SVM) of a permanent magnet synchronous motor (PMSM) powered by a photovoltaic (PV) source. In the conventional direct torque control (DTC) of a permanent magnet synchronous motor (PMSM), hysteresis controllers are used to choose the proper voltage vector resulting in large torque ripples. The direct torque control can accelerate the torque responses but increases the torque ripple at same time. Nowadays, exist some other alternative approaches to reduce the torque ripples based on (Predictive SVM) technique. This method is based on the replacement of hysteresis comparators (used in conventional DTC) by Proportional Integral (PI) regulators and the selection table by space vector modulation (SVM). The simulation results confirm that this proposed method where the control of the switching frequency is well controlled, allows us to reduce the oscillations of the electromagnetic torque and flux by 20 % and 30%, respectively with a good dynamic response compared with conventional DTC

Databases and Information Systems in the AI Era: Contributions from ADBIS, TPDL and EDA 2020 Workshops and Doctoral Consortium

Research on database and information technologies has been rapidly evolving over the last couple of years. This evolution was lead by three major forces: Big Data, AI and Connected World that open the door to innovative research directions and challenges, yet exploiting four main areas: (i) computational and storage resource modeling and organization; (ii) new programming models, (iii) processing power and (iv) new applications that emerge related to health, environment, education, Cultural Heritage, Banking, etc. The 24th East-European Conference on Advances in Databases and Information Systems (ADBIS 2020), the 24th International Conference on Theory and Practice of Digital Libraries (TPDL 2020) and the 16th Workshop on Business Intelligence and Big Data (EDA 2020), held during August 25–27, 2020, at Lyon, France, and associated satellite events aimed at covering some emerging issues related to database and information system research in these areas. The aim of this paper is to present such events, their motivations, and topics of interest, as well as briefly outline the papers selected for presentations. The selected papers will then be included in the remainder of this volume

Multiple Decisional Query Optimization in Big Data Warehouse

International audienc

OLAP Visualization Operator for Complex Data

Abstract. Data warehouses and Online Analysis Processing (OLAP) have acknowledged and efficient solutions for helping in the decisionmaking process. Through OLAP operators, online analysis enables the decision-maker to navigate and view data represented in a multi-dimensional manner. But when the data or objects to be analyzed are complex, it is necessary to redefine and enhance the abilities of the OLAP. In this paper, we suggest combining OLAP and data mining in order to create a new visualization operator for complex data or objects. This operator uses the correspondence analysis method and we call it VOCoDa (Visualization Operator for Complex Data)

OLAP on Complex Data : Visualization Operator Based on Correspondance Analysis

International audienceData warehouses and Online Analysis Processing (OLAP) have acknowledged and efficient solutions for helping in the decision-making process. Through OLAP operators, online analysis enables the decision-maker to navigate and view data represented in a multidimensional manner. But when the data or objects to be analyzed are complex, it is necessary to redefine and enhance the abilities of the OLAP. In this paper, we suggest combining OLAP and data mining in order to create a new visualization operator for complex data or objects. This operator uses the correspondence analysis method and we call it VOCoDa (Visualization Operator for Complex Data)