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Physical Human Activity Recognition Using Wearable Sensors
This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and wereExpand
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  • Open Access
An Unsupervised Approach for Automatic Activity Recognition Based on Hidden Markov Model Regression
Using supervised machine learning approaches to recognize human activities from on-body wearable accelerometers generally requires a large amount of labeled data. When ground truth information is notExpand
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  • Open Access
Learning from partially supervised data using mixture models and belief functions
This paper addresses classification problems in which the class membership of training data are only partially known. Each learning sample is assumed to consist of a feature vector x"[emailExpand
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Fault diagnosis in railway track circuits using Dempster-Shafer classifier fusion
This paper addresses the problem of fault detection and isolation in railway track circuits. A track circuit can be considered as a large-scale system composed of a series of trimming capacitorsExpand
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Clustering Smart Card Data for Urban Mobility Analysis
Smart card data gathered by automated fare collection (AFC) systems are valuable resources for studying urban mobility. In this paper, we propose two approaches to cluster smart card data, which canExpand
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Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris
Today, more and more bicycle sharing systems (BSSs) are being introduced in big cities. These transportation systems generate sizable transportation data, the mining of which can reveal theExpand
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  • Open Access
Understanding Passenger Patterns in Public Transit Through Smart Card and Socioeconomic Data: A case study in Rennes, France
Data collected by Automated Fare Collection (AFC) systems are a valuable resource for studying the travel habits of large city inhabitants. In this paper, we present an approach to mining theExpand
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Mixture-model-based signal denoising
This paper proposes a new signal denoising methodology for dealing with asymmetrical noises. The adopted strategy is based on a regression model where the noise is supposed to be additive andExpand
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Forecasting dynamic public transport Origin-Destination matrices with long-Short term Memory recurrent neural networks
A considerable number of studies have been undertaken on using smart card data to analyse urban mobility. Most of these studies aim to identify recurrent passenger habits, reveal mobility patterns,Expand
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DEDICATED SENSOR AND CLASSIFIER OF RAIL HEAD DEFECTS
Abstract This paper presents an original system based on a specialized eddy-current sensor for the inspection of railway tracks. The device aims at the detection of broken rails and large head spallsExpand
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