Latifa Oukhellou

Latifa Oukhellou
Université Gustave Eiffel · COSYS/GRETTIA

PhD Université Paris Sud, HDR Université Paris-Est

About

132
Publications
23,517
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
2,539
Citations
Additional affiliations
September 2011 - present
University of Paris-Est
Position
  • Directrice de Recherche
September 1998 - August 2011

Publications

Publications (132)
Article
Clustering is used in many applicative fields to organize data into a few groups. Motivated by behavioral extraction issues from urban data, this paper proposes a new clustering method to model clusters with dynamic profiles while considering common regressive effects. As maximum likelihood estimation is not suitable in this case, the parameters of...
Article
Full-text available
The increase in the amount of data collected in the transport domain can greatly benefit mobility studies and create high value-added mobility information for passengers, data analysts, and transport operators. This work concerns the detection of the impact of disturbances on a transport network. It aims, from smart card data analysis, to finely qu...
Article
Mobility demand analysis is increasingly based on smart card data, that are generally aggregated into time series describing the volume of riders along time. These series present patterns resulting from multiple external factors. This paper investigates the problem of decomposing daily ridership data collected at a multimodal transportation hub. Th...
Article
Full-text available
Developing an efficient short-term prediction framework for public transportation systems is of fundamental importance. This paper proposes a new image-processing-oriented methodology for the short-term prediction of train loads. First, we introduce a novel approach for representing the metro traffic by generating an image, exhibiting the spatial i...
Article
Categorical sequences are widely used in various domains to describe the evolutionary state of the process under study. This article addresses the problem of behavioral change detection for multiple categorical time series. Relying on the sequential likelihood ratio test, an online change detection method is proposed based on the joint modeling of...
Book
The analysis of massive amounts of data collected via smart grids can contribute to manage more efficiently energy production and water resources. Within this framework, a method is proposed in this article to detect changes in panel data from smart electricity and water networks. The adopted approach is based on a representation of the data by clu...
Article
Full-text available
The understanding of rider/vehicle interaction modalities remains an issue, specifically in the case of bend-taking. This difficulty results both from the lack of adequate instrumentation to conduct this type of study and from the variety of practices of this population of road users. Riders have numerous explanations of strategies for controlling...
Preprint
Full-text available
One of the major goals of transport operators is to adapt the transport supply scheduling to the passenger demand for existing transport networks during each specific period. Another problem mentioned by operators is accurately estimating the demand for disposable ticket or pass to adapt ticket availability to passenger demand. In this context, we...
Article
Full-text available
Soiling losses are a major concern for remote power systems that rely on photovoltaic energy. Power loss analysis is efficient for the monitoring of large power plants and for developing an optimal cleaning schedule, but it is not adapted for remote monitoring of standalone photovoltaic systems that are used in rural and poor regions. Indeed, this...
Chapter
The increase in the amount of data collected in the transport domain can greatly benefit mobility studies and help to create high value-added mobility services for passengers as well as regulation tools for operators. The research detailed in this paper is related to the development of an advanced machine learning approach with the aim of forecasti...
Article
Full-text available
The emergence of smart meters has fostered the collection of massive data that support a better understanding of consumer behaviors and better management of water resources and networks. The main focus of this paper is to analyze consumption behavior over time; thus, we first identify the main weekly consumption patterns. This approach allows each...
Article
Full-text available
This article presents a machine learning methodology for diagnosing Parkinson’s disease (PD) based on the use of vertical Ground Reaction Forces (vGRFs) data collected from the gait cycle. A classification engine assigns subjects to healthy or Parkinsonian classes. The diagnosis process involves four steps: data pre-processing, feature extraction a...
Article
Dans le domaine de la mobilité, les travaux de recherche visent à mieux comprendre les pratiques de mobilité et la manière dont elles s'articulent à des territoires urbains. L'ouverture des données pose une question essentielle : Quels apports de connaissances sur nos mobilités et nos villes ces nouvelles données offrent-elles ? Et dans quelle mesu...
Article
This paper aims to analyse the intermodal practices of mobility in the bus-metro network of Rennes metropole. Intermodality being strongly linked to the use of urban public transport networks, the Rennes Métropole bus and metro network data provided by Keolis-Rennes provides a very significant part of daily intermodality. To compensate for the lack...
Article
This paper aims to analyse the intermodal practices of mobility in the bus-metro network of Rennes metropole. Intermodality being strongly linked to the use of urban public transport networks, the Rennes Métropole bus and metro network data provided by Keolis-Rennes provides a very significant part of daily intermodality. To compensate for the lack...
Article
Driving errors are considered to be the greatest contributory cause in all road accidents and an important contributory cause of most fatal accidents. This is particularly the case for the users of powered two-wheeled vehicles (PTWs), perhaps because PTW riders play a greater role in the control of their vehicles' stability than four-wheeled vehicl...
Article
Full-text available
The large amount of data collected by smart meters is a valuable resource that can be used to better understand consumer behavior and optimize electricity consumption in cities. This paper presents an unsupervised classification approach for extracting typical consumption patterns from data generated by smart electric meters. The proposed approach...
Technical Report
Full-text available
Le projet Mobilletic vise à valoriser les données billetti-ques des transports publics par une approche multidis-ciplinaire revisitant les liens qu'entretiennent les sciences humaines et sociales et les data sciences. La question de la valorisation de données massives pour la prise de décision est en effet centrale. L'ambition a été de proposer des...
Article
In recent years, there has been increased interest in using completely anonymized data from smart card collection systems to better understand the behavioural habits of public transport passengers. Such an understanding can benefit urban transport planners as well as urban modelling by providing simulation models with realistic mobility patterns of...
Article
La directrice générale de l'Ifsttar s'exprime sur les questions suivantes : Quelle est votre 'vision' de la mobilité intelligente ? Quels sont les axes stratégiques de l'IFSTTAR en matière de mobilité ? Dans ces domaines, sur quels programmes ou projets de recherche précis travaillez-vous ? De quelle manière le monde de la recherche et le monde ind...
Article
Posture analysis in quiet standing is an essential element in evaluating human balance control. Many factors enhance the human control system's ability to maintain stability, such as the visual system and base of support (feet) placement. In contrast, many neural pathologies, such as Parkinson's disease (PD) and cerebellar disorder, disturb human s...
Conference Paper
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, reconstruct and predict passenger flows, etc. Forecasting mobility demand is a central problem for public transport authorities and operators alike. It...
Article
Smart card data gathered by Automated Fare Collection (AFC) systems are a valuable resource for studying urban mobility. In this paper, we propose two approaches to clustering smart card data that can be used to extract mobility patterns in a public transportation system. Two complementary standpoints are considered: a station-oriented, operational...
Article
To achieve a fast and low cost diagnostic, we propose a new tool based on wavelet leaders in which the proton exchange membrane fuel cell (PEMFC) diagnosis is made by the observation of the one and only stack voltage. The steps of our strategy are the following ones: (i) the PEMFC is operated under a variety of conditions (nominal or severe) using...
Article
Full-text available
Smartcard data provide a great number of information that are increasingly used nowadays. In the field of transport, they offer the opportunity to study passenger behavior, leading to a better knowledge of public transit demand and thereby granting the transport operators the ability to adapt their transport offer and services accordingly, both in...
Article
Fuel Cell aging monitoring and diagnosis are key-issues for scientists and industrials who intend to spread this technology. In the present work, we propose an efficient method that enables the extraction of valuable information which contains indicators on the aging of a studied PEM Fuel Cell (PEMFC). In this context, we investigate the possibilit...
Article
In mission-critical wireless sensor networks surveillance applications, a high detection rate coupled with a low false alarm rate is essential. Additionally, fusion methods can be employed with the hope that aggregation of uncertain information from multiple sensors enhances the quality of surveillance provided by the network. This paper investigat...
Article
Full-text available
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 were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recogniti...
Article
ICMLA 2015 - IEEE International Conference on Machine Learning and Applications, MIAMI, ETATS-UNIS, 09-/12/2015 - 11/12/2015
Article
Full-text available
This paper presents the application of clustering algorithms to daily energy consumption curves of buildings. Our aim is to identify a reduced set of consumption patterns for a tertiary building during one year. These patterns depend on the temperature throughout the year as well as the type of the day (working day, work-free day and school holiday...
Article
ESANN 2015 - 23rd European Symposium on Artificial Neural Networks, BRUGES, BELGIQUE, 22-/04/2015 - 24/04/2015
Article
De nouvelles sources d'information telles que les données billettiques permettent de proposer d'autres approches pour étudier la mobilité dans les transports en commun. À travers un cas d'étude mené sur Rennes Métropole, nous illustrons comment ces données peuvent être exploitées afin d'extraire des connaissances permettant de caractériser finement...
Article
The emergence of new technologies allows better monitoring of traffic conditions and understanding of urban network dynamics. Bluetooth technology is becoming widespread, as it represents a cost-effective means for capturing road traffic in both arterials and motorways. Although the extraction of travel time from Bluetooth data is fairly straightfo...
Article
The study summarized in this paper deals with non-intrusive fault diagnosis of Polymer Electrolyte Membrane Fuel Cell (PEMFC) stack. In the proposed approach, the diagnosis operation is based on the stack voltage singularity measurement and classification. To this aim, wavelet transform-based multifractal formalism, named WTMM (Wavelet Transform Mo...
Conference Paper
This paper presents a simple and efficient methodology that uses both acceleration and angular velocity signals to detect a fall of Powered Two Wheelers (PTW). Detecting the rider's fall (before the impact of the rider on the ground) can indeed be used to provide a signal in order to trigger inflation of an airbag jacket worn by the rider, reducing...
Article
Studies on human mobility, including Bike Sharing System Analysis, have expanded over the past few years. They aim to give insight into the underlying urban phenomena linked to city dynamics and generally rely on data-mining tools to extract meaningful patterns from the huge volume of data recorded by such complex systems. This paper presents one s...
Article
Full-text available
Today, more and more bicycle sharing systems (BSS) are being introduced in big cities. These transportation systems generate sizable transportation data, the mining of which can reveal the underlying urban phenomena linked to city dynamics. This paper presents a statistical model to automatically analyze the trips data of a bike sharing system. The...
Article
The analysis and monitoring of the human daily living activities plays an important role for rehabilitation goals, fall prevention rehabilitation and general health-care treatments. Among these activities, walking is the most important daily motion. Studying the evolution of the gait cycle through the analysis of the human center of force is benefi...
Conference Paper
In order to meet the mounting social and economic demands, railway operators and manufacturers are striving for a longer availability and a better reliability of railway transportation systems. Commercial trains are equipped with state-of-the-art onboard intelligent sensors monitoring various subsystems all over the train such as tilt, traction, si...
Article
In this paper, a machine-learning framework is used for riding pattern recognition. The problem is formulated as a classification task to identify the class of riding patterns using data collected from 3-D accelerometer/gyroscope sensors mounted on motorcycles. These measurements constitute an experimental database used to analyze powered two-wheel...
Conference Paper
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 the temporal behavior of the passengers in a public transportation system in order to extract relevant and eas- ily interpretable clusters. Such classi�cation can...
Article
Full-text available
p>Nous nous proposons d'exploiter les informations révélées par la morphologie du signal de la tension d'une pile à combustible (PàC) de type PEM afin de développer un outil de diagnostic. L'essentiel de l'information contenue dans un signal " rugueux " se situe souvent dans ses singularités et ses structures irrégulières ; la méthode des ondelette...
Article
This paper deals with fault diagnosis of a Proton Exchange Membrane Fuel Cell (PEMFC) using a supervised method of classification coupled with Electrochemical Impedance Spectroscopy (EIS). The purpose is to be able to detect if the fuel cell is in abnormal operating conditions and also to isolate the fault. To reach this aim, a classification metho...
Article
In this paper, a fault diagnosis of a Proton Exchange Membrane Fuel Cell (PEMFC) is presented. The aim of this tool is to avoid non reversible degradations of a fuel cell system linked to fault occurrence. The damage incurred by the fuel cell depends on the nature of the fault and its duration time. Some faults are non-reversibles for the fuel cell...
Article
This study used data from 3D Inertial Measurement Unit (accelerometers/gyroscopes) mounted on the Powered Two Wheelers (PTW) to analyze and classify PTW rider’s behavior. In our work, we hypothesize that by learning riding patterns, useful information pertaining to the conditions of riding environment can be provided for riders in order to assist t...
Article
Full-text available
In the last few years, Dempster–Shafer theory also known as Theory of Belief Functions (TBF) or Evidence theory has received growing attention in many fields of applications such as finance, technology, biomedicine, etc. This theory may be seen as a generalization framework of different instances such as probability, fuzzy sets, and possibility the...
Article
Full-text available
In the last few years, evidence theory, also known as Dempster-Shafer theory or belief functions theory, have received growing attention in many fields such as artificial intelligence, computer vision, telecommunications and networks, robotics, and finance. This is due to the fact that imperfect information permeates the real-world applications, an...
Article
Measuring local singularities on voltage signal transmits valuable information about the evolving dynamics of non-stationary and nonlinear processes in fuel cell systems. This paper deals with wavelet transform combined with multifractal formalism proposed for PEMFC behavior analysis. The proposed method combines the capability of wavelet transform...
Article
We focus on predicting demands of bicycle usage in Velib system of Paris, which is a large-scale bicycle sharing service covering the whole Paris and its near suburbs. In this system, bicycle demand of each station usually correlates with historical Velib usage records at both spatial and temporal scale. The spatio-temporal correlation acts as an i...
Article
Full-text available
This paper deals with a data mining approach applied on Bike Sharing System Origin-Destination data, but part of the proposed methodology can be used to analyze other modes of transport that similarly generate Dynamic Origin-Destination (OD) matrices. The transportation network investigated in this paper is the Vélib’ Bike Sharing System (BSS) syst...
Article
Full-text available
This paper describes a pattern recognition approach aiming to estimate fuel cell duration time from electrochemical impedance spectroscopy measurements. It consists in first extracting features from both real and imaginary parts of the impedance spectrum. A parametric model is considered in the case of the real part, whereas regression model with l...
Article
Full-text available
The problem of human activity recognition is central for understanding and predicting the human behavior, in particular in a prospective of assistive services to humans, such as health monitoring, well being, security, etc. There is therefore a growing need to build accurate models which can take into account the variability of the human activities...
Article
Full-text available
Using supervised machine learning approaches to recognize human activities from on-body wearable accelerometers generally requires a large amount of labelled data. When ground truth information is not available, too expensive, time consuming or difficult to collect, one has to rely on unsupervised approaches. This paper presents a new unsupervised...
Article
The study summarized in this paper proposes a new tool for PEMFC non-intrusive diagnosis based on voltage singularity measurement and classification. The method takes advantage of the non-linearities associated with discontinuities introduced in the dynamic response data resulting from various failure modes. Continuous wavelets and multifractal for...
Conference Paper
In order to meet the mounting social and economic demands, railway operators and manufacturers are striving for a longer availability and a better reliability of railway transportation systems. Commercial trains are being equipped with state-of-the-art onboard intelligent sensors monitoring various subsystems all over the train. These sensors provi...
Conference Paper
Full-text available
Considering availability purposes for train transportation, passenger accesses (doors and steps) are often designated as critical systems. To improve global availability of its rolling stock, Bombardier Transportation (BT) aims at reinforcing its maintenance procedure by introducing predictive diagnosis. The SURFER project has been initiated to dev...
Article
Full-text available
The increasing demand on railway transportation due to social, economic and demographic factors has triggered an evolution in preventive maintenance strategies towards more optimized and cost-effective processes. Within this context related to the increasing interest in predictive maintenance strategies, commercial trains are being equipped with bo...
Conference Paper
In this paper, we develop a simple and efficient methodology for riding patterns recognition based on a machine learning framework. The riding pattern recognition problem is formulated as a classification problem aiming to identify the class of the riding situation by using data collected from three-accelerometer and three-gyroscope sensors mounted...