Search results for "Edge"
showing 10 items of 3866 documents
LC3: A spatio-temporal and semantic model for knowledge discovery from geospatial datasets
2015
International audience; There is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a mo…
A Conceptual Architecture of Ontology Based KM System for Failure Mode and Effects Analysis
2014
Failure Mode and Effects Analysis (FMEA) is a systematic method for procedure analyses and risk assessment. It is a structured way to identify potential failure modes of a product or process, probability of their occurrence, and their overall effects. The basic purpose of this analysis is to mitigate the risk and the impact associated to a failure by planning and prioritizing actions to make a product or a process robust to failure. Effective manufacturing and improved quality products are the fruits of successful implementation of FMEA. During this activity valuable knowledge is generated which turns into product or process quality and efficiency. If this knowledge can be shared and reused…
Ant Colony Models for a Virtual Educational Environment Based on a Multi-Agent System
2008
We have designed a virtual learning environment where students interact through their computers and with the software agents in order to achieve a common educational goal. The Multi-Agent System (MAS) consisting of autonomous, cognitive and social agents communicating by messages is used to provide a group decision support system for the learning environment. Learning objects are distributed in a network and have different weights in function of their relevance to a specific educational goal. The relevance of a learning object can change in time; it is affected by students', agents' and teachers' evaluation. We have used an ant colony behavior model for the agents that play the role of a tu…
A synthesis regarding the application of Expert Systems in Inventory management
2015
The paper surveys the application of Expert Systems in Inventory field in order to find out the relevant aspects needed to build an improved system. The result is a hybrid Expert System-Decision Support System that helps managers to face the uncertainty, complexity and the dynamics of the Inventory Management as the Heart of the Supply Chain Management.
Emotional Business Intelligence
2014
The domain of Emotional Business Intelligence (EBI) aims to support business-relevant emotional and emotion-aware decisions in addition to rational decision making. EBI originates from three root domains: Emotional Business, Emotional Intelligence and Business Intelligence (BI). In this paper we emphasize emotional empowerment of the traditional BI function; outline its main characteristics as a business working model of an emotionally smart, continuously learning organization; and introduce a first candidate of the EBI Toolkit, the FeelingsExplorer (FE). FE is a mash-up browser based on 4i (“ForEye”) technology, capable of visualizing objects in an emotional semantic space and thereby supp…
A Knowledge Based Decision Support System for Bioinformatics and System Biology
2011
In this paper, we present a new Decision Support System for Bioinformatics and System Biology issues. Our system is based on a Knowledge base, representing the expertise about the application domain, and a Reasoner. The Reasoner, consulting the Knowledge base and according to the user’s request, is able to suggest one or more strategies in order to resolve the selected problem. Moreover, the system can build, at different abstraction layers, a workflow for the current problem on the basis of the user’s choices, freeing the user from implementation details and assisting him in the correct configuration of the algorithms. Two possible application scenarios will be introduced: the analysis of …
A knowledge-based decision support system in bioinformatics: An application to protein complex extraction
2013
Abstract Background We introduce a Knowledge-based Decision Support System (KDSS) in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB) coding the expertise about the proposed scenario, our KDSS is able to suggest both strategies and tools, according to the features of input dataset. Our system provides a navigable workflow for the current experiment and furthermore it offers support in the configuration and running of every processing component of that workflow. This last feature makes our system a crossover between classical DSS and Workflow Management Systems. Results We briefly present the KDSS' architecture and basic concepts used in the design of the knowl…
Feature extraction for classification in knowledge discovery systems
2003
Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of "the curse of dimensionality". We consider three different eigenvector-based feature extraction approaches for classification. The summary of obtained results concerning the accuracy of classification schemes is presented and the issue of search for the most appropriate feature extraction method for a given data set is considered. A decision support system to aid in the integration of the feature extraction and classification processes is proposed. The goals and requirements set for the d…
Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P
2016
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model-theoretic probabilistic reasoning and to default reasoning in System P. In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System P. That is, we provide a new probabilistic semantics for System P, which neither uses infinitesimal probabilities nor atomic bound (or bi…
Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning
2001
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…