Search Results - "Oukhellou, L."

Joint segmentation of multivariate time series with hidden process regression for human activity recognition by Chamroukhi, F., Mohammed, S., Trabelsi, D., Oukhellou, L., Amirat, Y.

“…The problem of human activity recognition is central for understanding and predicting the human behavior, in particular in a prospective of assistive services…”
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Learning from partially supervised data using mixture models and belief functions by Côme, E., Oukhellou, L., Denœux, T., Aknin, P.

“…This paper addresses classification problems in which the class membership of training data are only partially known. Each learning sample is assumed to…”
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PEMFC stack voltage singularity measurement and fault classification by BENOUIOUA, D, CANDUSSO, D, HAREL, F, OUKHELLOU, L

“…The study summarized in this paper deals with non-intrusive fault diagnosis of Polymer Electrolyte Membrane Fuel Cell (PEMFC) stack. In the proposed approach,…”
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Fuel cell diagnosis method based on multifractal analysis of stack voltage signal by Benouioua, D., Candusso, D., Harel, F., Oukhellou, L.

“…Measuring local singularities on voltage signal transmits valuable information about the evolving dynamics of non-stationary and nonlinear processes in fuel…”
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The dynamic multifractality in PEMFC stack voltage signal as a tool for the aging monitoring by Benouioua, D., Candusso, D., Harel, F., Oukhellou, L.

“…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…”
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Fuel cells static and dynamic characterizations as tools for the estimation of their ageing time by Onanena, R., Oukhellou, L., Candusso, D., Harel, F., Hissel, D., Aknin, P.

“…This paper deals with a pattern-recognition-based diagnosis approach, which aim is to estimate the Fuel Cell (FC) operating time, and consequently its…”
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Multifractal Analysis of Stack Voltage Based on Wavelet Leaders: A New Tool for PEMFC Diagnosis by Benouioua, D., Candusso, D., Harel, F., Oukhellou, L.

“…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…”
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Estimation of fuel cell operating time for predictive maintenance strategies by Onanena, R., Oukhellou, L., Candusso, D., Same, A., Hissel, D., Aknin, P.

“…Durability is one of the limiting factors for spreading and commercialization of fuel cell technology. That is why research to extend fuel cell durability is…”
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Combined use of sensor data and structural knowledge processed by Bayesian network: Application to a railway diagnosis aid scheme by Oukhellou, L., Côme, E., Bouillaut, L., Aknin, P.

“…This article describes a hybrid diagnosis system based on the combined use of sensor data (local information) and structural knowledge (global information)…”
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Analyzing year-to-year changes in public transport passenger behaviour using smart card data by Briand, Anne-Sarah, Côme, Etienne, Trépanier, Martin, Oukhellou, Latifa

“…•Clustering of passenger cards using continuous temporal activities.•The replicability of the approach proposed by Briand et al. (2016) is…”
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From energy behaviours to lifestyles: contribution of behavioural archetypes to the description of energy consumption patterns in the residential sector by Heinrich, M., Ruellan, M., Oukhellou, L., Samé, A., Lévy, J-P.

“…•The segmentation of households according to their residential behaviour is explored.•The methodology makes use of mixed data and promotes comparability.•7…”
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Combined use of partial least squares regression and neural network for diagnosis tasks by Debiolles, A., Oukhellou, L., Aknin, P.

“…This work deals with a diagnosis system, based on a combined use of partial least squares regression (PLS) and neural network (NN). An application concerning…”
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An Unsupervised Approach for Automatic Activity Recognition Based on Hidden Markov Model Regression by Trabelsi, Dorra, Mohammed, Samer, Chamroukhi, Faicel, Oukhellou, Latifa, Amirat, Yacine

“…Using supervised machine learning approaches to recognize human activities from on-body wearable accelerometers generally requires a large amount of labeled…”
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WSNs deployment framework based on the theory of belief functions by Senouci, M. R., Mellouk, A, Oukhellou, L., Aissani, A.

“…Deployment is a fundamental issue in Wireless Sensor Networks (WSNs). Indeed, the number and locations of sensors determine the topology of the WSN, which will…”
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An Evidence-Based Sensor Coverage Model by Senouci, M. R., Mellouk, A., Oukhellou, L., Aissani, A.

“…A key challenge in the success of wireless sensor networks deployment is to consider the imperfections associated with sensor readings. Existing sensor…”
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Automatic Segmentation of Stabilometric Signals Using Hidden Markov Model Regression by Safi, Khaled, Mohammed, Samer, Attal, Ferhat, Amirat, Yacine, Oukhellou, Latifa, Khalil, Mohamad, Gracies, Jean-Michel, Hutin, Emilie

“…Posture analysis in quiet standing is an essential element in evaluating human balance control. Many factors enhance the human control system's ability to…”
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Foreword: Belief functions and uncertainty management in networks and telecommunication by Mellouk, A, Oukhellou, L., Shu, L., Shafer, G.

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Belief Functions in Telecommunications and Network Technologies: An Overview by Senouci, M. R., Mellouk, A, Senouci, A., Oukhellou, L.

“…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…”
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Scanning the Issue by Ioannou, P., Sun, J., Li, T., Yu, M., Zhang, H.M., Zheng, F., Man, X., Chu, F., Liu, M., Chu, C., Clark, K.L., Bhatia, U., Kodra, E.A., Ganguly, A.R., Wandelt, S., Sun, X., Fricke, H., Yi, Z., Bauer, P.H., Kim, W., Kang, C.M., Son, Y.S., Lee, S., Chung, C.C., Adacher, L., Flamini, M., Romano, E., Hartley, R., Kamgar-Parsi, B., Narber, C., Brecht, B., Therriault, D., Weimerskirch, A., Whyte, W., Kumar, V., Hehn, T., Goudy, R., Ma, C., Xue, J., Liu, Y., Yang, J., Li, Y., Zheng, N., Zhang, Z., Xing, C., Xiao, H., Abdollahi Biron, Z., Dey, S., Pisu, P., Zhan, H., Gomes, G., Li, X.S., Madduri, K., Sim, A., Wu, K., Hasan, K.F., Feng, Y., Tian, Y., Iranmanesh, S.M., Mahjoub, H.N., Kazemi, H., Fallah, Y.P., Zhang, Y., Chen, C., Wu, Q., Lu, Q., Zhang, S., Zhang, G., Yang, Y., Liu, P., Yang, L., Gao, Z., Huang, Y., Li, S., Gao, Y., Soatti, G., Nicoli, M., Garcia, N., Denis, B., Raulefs, R., Wymeersch, H., Wang, J., Wang, X., Dolan, J.M., Herrmann, A., Pilla, F., Shorten, R., Lee, C., Moon, J.-H., Ding, F., Jin, H., Attal, F., Boubezoul, A., Same, A., Oukhellou, L., Espie, S., Tang, K., Chen, S., Liu, Z., Goya, J.

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Scanning the Issue by Ioannou, P., Li, T., Yu, M., Zhang, H.M., Zheng, F., Man, X., Chu, F., Liu, M., Chu, C., Clark, K.L., Bhatia, U., Kodra, E.A., Ganguly, A.R., Wandelt, S., Sun, X., Fricke, H., Bauer, P.H., Kim, W., Kang, C.M., Son, Y.S., Lee, S., Chung, C.C., Flamini, M., Romano, E., Hartley, R., Kamgar-Parsi, B., Narber, C., Brecht, B., Therriault, D., Whyte, W., Kumar, V., Hehn, T., Goudy, R., Ma, C., Xue, J., Liu, Y., Yang, J., Li, Y., Zheng, N., Sun, J., Zhang, Z., Xing, C., Xiao, H., Abdollahi Biron, Z., Dey, S., Pisu, P., Zhan, H., Gomes, G., Li, X.S., Madduri, K., Sim, A., Wu, K., Hasan, K.F., Feng, Y., Iranmanesh, S.M., Mahjoub, H.N., Kazemi, H., Fallah, Y.P., Zhang, Y., Chen, C., Wu, Q., Lu, Q., Zhang, S., Zhang, G., Yang, Y., Liu, P., Yang, L., Gao, Z., Huang, Y., Gao, Y., Soatti, G., Nicoli, M., Garcia, N., Denis, B., Raulefs, R., Wymeersch, H., Zhang, Y., Wang, J., Wang, X., Dolan, J.M., Herrmann, A., Liu, M., Shorten, R., Lee, C., Moon, J.-H., Ding, F., Jin, H., Boubezoul, A., Same, A., Oukhellou, L., Espie, S., Tang, K., Chen, S., Liu, Z., Goya, J., De Miguel, G., Arrizabalaga, S., Zamora-Cadenas, L., Adin, I., Mendizabal, J.

“…Summary form only. Provides an overview of the technical articles and features of interest to readers that appear outside of this publication…”
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