Search results for "artificial intelligence"
showing 10 items of 6122 documents
A Neural Network Meta-Model and its Application for Manufacturing
2015
International audience; Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and flexibility of their operations. Manufacturers, as well as other industries, have successfully applied a promising statistical learning technique, called neural networks (NNs), to extract meaningful information from large data sets, so called big data. However, the application of NN to manufacturing problems remains limited because it involves the specialized skills of a data scientist. This paper introduces an appr…
Know Beyond Seeing: Combining Computer Vision with Semantic Reasoning
2018
International audience; To date, computer vision systems are limited to extract the digital data of what the cameras "see". However, the meaning of what they observe could be greatly enhanced by considering the environment and common-sense knowledge. A new approach to combine computer vision with semantic modeling has been developed. This approach extracts the knowledge from images and uses it to perform real-time reasoning according to the contextual information, events of interest and logic rules. The reasoning with image knowledge allows protecting the privacy of the users, to overcome some problems of computer vision such as occlusion and missed detections and to offer services such as …
Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks
2023
Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases th…
A Use Case of Data Integration in Food Production
2018
International audience; This paper presents a use case about knowledge representation and integration of data from different domains in food science. An ontology named PO 2 DG, the Process and Observation Ontology for the production of Dairy Gels, has been designed in order to provide a shared vocabulary for domain experts. The available data have been semantically structured using PO 2 DG and are stored in an RDF repository named PO 2 DG dataset. This use case identifies some of the challenges when dealing with a multi domain representation problem, gives some hints about possible solutions and suggests some further work.
Le grand débat national, une aide pour prendre des décisions locales?
2021
The Great National Debate, decided by Emmanuel Macron at the beginning of 2019 to respond to the Yellow Vests social movement, allowed the collection of citizens’ contributions on the ecological transition via an online platform. In this article, we use the corpus constituted by these contributions to identify areas where participants are asking for the development of bicycle paths and railway facilities. For this purpose, we have created a classification model to identify contributions dealing with the theme of transportation and proposed a method for extracting patterns that reflect the contributors’ proposals. We then represented these patterns on maps, using the contributors’ postal cod…
SEMANTIC WEB TECHNOLOGIES FOR IMPLEMENTING COST-EFFECTIVE AND INTEROPERABLE BUILDING INFORMATION MODELING
2015
International audience; In the field of AEC/FM, BIM has been recognized by industrial and political actors as a powerful tool for resolving data interoperability problems. Coupled with cloud computing and GIS, BIM would allow integrating different information exchange standard into one single digital building model that can be real-time edited by several stakeholders or architects. In this paper, we examine the benefits brought by using Semantic Web technologies in delivering such universal building model. We present how our approach is a step further in reaching the vision of BIM, and how it can serve construction process, operation and maintenance, along with facilities’ lifecycle managem…
A spatially explicit model to simulate soil microbial communities’ dynamics at an agricultural landscape scale
2021
Soil microorganisms play a major role in soil functions and are an efficient indicator to evaluate the impact of agricultural practices on soil quality. Biogeographical studies over wide scales ranging from landscape to countries have concluded that soil microbial abundance and soil prokaryotic richness is following a heterogeneous distribution in space under the dependence of soil properties (e.g. pH, soil texture, organic matter content) and agricultural practices. The goal of this study is the creation of a model that can predict dynamics of soil microbial communities depending on the agricultural management over time. For this, we focus on a monitored landscape (Fénay landscape, 1.200 h…
Bridging Sensing and Decision Making in Ambient Intelligence Environments
2009
Context-aware and Ambient Intelligence environments represent one of the emerging issues in the last decade. In such intelligent environments, information is gathered to provide, on one hand, autonomic and easy to manage applications, and, on the other, secured access controlled environments. Several approaches have been defined in the literature to describe context-aware application with techniques to capture and represent information related to a specified domain. However and to the best of our knowledge, none has questioned the reliability of the techniques used to extract meaningful knowledge needed for decision making especially if the information captured is of multimedia types (image…
Modeling and Coordination of interconnected microgrids using distributed artificial intelligence approaches
2019
As renewable sources penetrate the current electrical system to relief global warming and energy shortage, microgrid (MG) emerges to reduce the impact of intermittent generation on the utility grid. Additionally, it improves the automation and intelligence of the power grid with plug-and-play characteristics. Inserting more MGs into a distribution network promotes the development of the smart grid. Thus MG networks existing in the power system are in prospect. Coordinating them could gain a system with high reliability, low cost, and strong resistance to electrical faults. Achieving these profits relies on developed technologies of communication, control strategy, and corresponding algorith…
Incorporating depth information into few-shot semantic segmentation
2021
International audience; Few-shot segmentation presents a significant challengefor semantic scene understanding under limited supervision.Namely, this task targets at generalizing the segmentationability of the model to new categories given a few samples.In order to obtain complete scene information, we extend theRGB-centric methods to take advantage of complementary depthinformation. In this paper, we propose a two-stream deep neuralnetwork based on metric learning. Our method, known as RDNet,learns class-specific prototype representations within RGB anddepth embedding spaces, respectively. The learned prototypesprovide effective semantic guidance on the corresponding RGBand depth query ima…