Publications
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Deep transferable learning on heartbeat classification for imbalance dataset
Electrocardiogram (ECG) data recorded by medical devices are hard to analyze manually. Therefore, it is important to analyze and categorize each heartbeat using machine learning. Recently, advancements in machine learning have made classification of complex data easy and fast. However, these machine learning algorithms require sufficient amount of training data and have limited performance in […]
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Conception universelle, lead user et intelligence émotionnelle
L’objet de cette conférence était de présenter les résultats de notre étude portant sur l’identification des caractéristiques des lead users, à soir l’empathie et la compétence dans le domaine.
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Impliquer les managers dans le développement des compétences de leurs équipes avec l’intégration de dynamiques apprenantes: construire des environnements capacitants
Comprendre comment l’idée d’environnement capacitant revisite les modalités de management
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Buckling of Timoshenko beam under two-parameter elastic foundations
This paper exposes buckling solutions of a plane, quasi-static Timoshenko beam with small transformation subjected to a longitudinal force and surrounded by an elastic wall modeled by two-parameter elastic foundations. A non-dimensional analysis of associated Haringx and Engesser model is performed and buckling stress and shape are exposed analytically. Relations for rigidity of the wall […]
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Community-based method for extracting backbones
Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major […]
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A new approach for removing point cloud outliers using the standard score
Cleaning data is one of the most important tasks in data science and machine learning. It solves many problems in datasets, such as time complexity, added noise, and so on. In a huge datasets, outliers are extreme values that deviate from an overall pattern on a sample. Usually, they indicate variability in measurements or experimental […]
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A new approach for removing point cloud outliers using box plot
Cleaning a point cloud building is challenging issue, it is crucial for a better representation of the scan-to-BIM 3D model. During the scan, the point cloud is in generally influenced by several factors. The scanner can provide false data due to reflections on reflective surfaces like mirrors, windows, etc. The false points can form a […]
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Improved Hourly Prediction of BIPV Photovoltaic Power Building Using Artificial Learning Machine: A Case Study
In the energy transition, controlling energy consumption is a challenge for everyone, especially for BIPV (Building Integrated Photovoltaics) buildings. Artificial Intelligence is an efficient tool to analyze fine prediction with a better accuracy. Intelligent sensors are implemented on the different equipments of a BIPV building to collect information and to take decision about the energy […]
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Functional and Dysfunctional modelling and assessment of an Emergency Responce Plan
The objective of crisis management is to limit the impact of a feared event that has occurred and to restore the conditions corresponding to a nominal situation. In this context, we will focus on emergency response plans for mass casualty crises. In this paper, we propose a functional modelling of the French generic emergency plan, […]
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Multi-agent Dynamic Planning for Crisis Rescue Plans
We are interested in rescue management in crises such as in terrorist attacks. Today, there are emergency plans that take into account all the stakeholders involved in a crisis depending on the event type, magnitude and place. Unfortunately, they do not anticipate the evolution of the crisis situation such as traffic and hospital overcrowding. In […]
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A CONNECTED MOBILITY SCHEME FOR TAXI SUPPLY-DEMAND BALANCING IN A SMART CITY CONTEXT
In this paper we present the preliminary results of simulation-based experiments of an integrated scheme that has been proposed to control taxi supply-demand imbalance in the context of a smart city with multiple taxi operators and using Connected Mobility. We particularly explore the difference between centralized and decentralized implementations of the scheme as well as […]
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