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Artykuły w czasopismach na temat "Estimation du flux de passagers"
Li, H. Y., i W. M. Yan. "Inverse Convection Problem for Determining Wall Heat Flux in Annular Duct Flow". Journal of Heat Transfer 122, nr 3 (29.02.2000): 460–64. http://dx.doi.org/10.1115/1.1287169.
Pełny tekst źródłaThapar, Vikram, i Fernando A. Escobedo. "Simultaneous estimation of free energies and rates using forward flux sampling and mean first passage times". Journal of Chemical Physics 143, nr 24 (28.12.2015): 244113. http://dx.doi.org/10.1063/1.4938248.
Pełny tekst źródłaPapadogianni, Vasiliki N., Alexandros Romeos, Athanasios Giannadakis, Konstantinos Perrakis i Thrassos Panidis. "Fire Ignition and Propagation in Hidden Zones of Aircrafts: A Novel Confined Fire Apparatus (CFA) for Flame Spreading Investigation". Fire 6, nr 8 (31.07.2023): 292. http://dx.doi.org/10.3390/fire6080292.
Pełny tekst źródłaTrentini, Anna, i Nicolas Malhene. "Maîtriser la coexistence des flux de passagers et de marchandises en milieu urbain". Revue Française de Gestion Industrielle 29, nr 2 (1.06.2010): 105–23. http://dx.doi.org/10.53102/2010.29.02.628.
Pełny tekst źródłaLin, Jingrou, Qingyang Sun, Yupeng Liu, Haijun Ye, Danling Tang, Xiaohao Zhang i Yang Gao. "Sea Surface pCO2 Response to Typhoon “Wind Pump” and Kuroshio Intrusion in the Northeastern South China Sea". Remote Sensing 16, nr 1 (27.12.2023): 123. http://dx.doi.org/10.3390/rs16010123.
Pełny tekst źródłaBhatt, Apoorva, Paweł Malecki i Dariusz Góra. "Shore Shadow Effect in Baikal". Universe 8, nr 7 (24.06.2022): 347. http://dx.doi.org/10.3390/universe8070347.
Pełny tekst źródłaChen, Changsheng, R. C. Beardsley, Song Hu, Qichun Xu i Huichan Lin. "Using MM5 to Hindcast the Ocean Surface Forcing Fields over the Gulf of Maine and Georges Bank Region*". Journal of Atmospheric and Oceanic Technology 22, nr 2 (1.02.2005): 131–45. http://dx.doi.org/10.1175/jtech-1682.1.
Pełny tekst źródłaGutiérrez-Jiménez, Eugenio, Changsi Cai, Irene Klærke Mikkelsen, Peter Mondrup Rasmussen, Hugo Angleys, Mads Merrild, Kim Mouridsen i in. "Effect of electrical forepaw stimulation on capillary transit-time heterogeneity (CTH)". Journal of Cerebral Blood Flow & Metabolism 36, nr 12 (21.07.2016): 2072–86. http://dx.doi.org/10.1177/0271678x16631560.
Pełny tekst źródłaStevenson, Ian H., Anil Cherian, Brian M. London, Nicholas A. Sachs, Eric Lindberg, Jacob Reimer, Marc W. Slutzky, Nicholas G. Hatsopoulos, Lee E. Miller i Konrad P. Kording. "Statistical assessment of the stability of neural movement representations". Journal of Neurophysiology 106, nr 2 (sierpień 2011): 764–74. http://dx.doi.org/10.1152/jn.00626.2010.
Pełny tekst źródłaVilleneuve, Paul. "Le Québec et l’intégration continentale : un processus à plusieurs vitesses et à directions multiples". Cahiers de géographie du Québec 41, nr 114 (12.04.2005): 337–47. http://dx.doi.org/10.7202/022672ar.
Pełny tekst źródłaRozprawy doktorskie na temat "Estimation du flux de passagers"
Drosouli, Ifigeneia. "Multimodal machine learning methods for pattern analysis in smart cities and transportation". Electronic Thesis or Diss., Limoges, 2024. http://www.theses.fr/2024LIMO0028.
Pełny tekst źródłaIn the context of modern, densely populated urban environments, the effective management of transportation and the structure of Intelligent Transportation Systems (ITSs) are paramount. The public transportation sector is currently undergoing a significant expansion and transformation with the objective of enhancing accessibility, accommodating larger passenger volumes without compromising travel quality, and embracing environmentally conscious and sustainable practices. Technological advancements, particularly in Artificial Intelligence (AI), Big Data Analytics (BDA), and Advanced Sensors (AS), have played a pivotal role in achieving these goals and contributing to the development, enhancement, and expansion of Intelligent Transportation Systems. This thesis addresses two critical challenges within the realm of smart cities, specifically focusing on the identification of transportation modes utilized by citizens at any given moment and the estimation and prediction of transportation flow within diverse transportation systems. In the context of the first challenge, two distinct approaches have been developed for Transportation Mode Detection. Firstly, a deep learning approach for the identification of eight transportation media is proposed, utilizing multimodal sensor data collected from user smartphones. This approach is based on a Long Short-Term Memory (LSTM) network and Bayesian optimization of model’s parameters. Through extensive experimental evaluation, the proposed approach demonstrates remarkably high recognition rates compared to a variety of machine learning approaches, including state-of-the-art methods. The thesis also delves into issues related to feature correlation and the impact of dimensionality reduction. The second approach involves a transformer-based model for transportation mode detection named TMD-BERT. This model processes the entire sequence of data, comprehends the importance of each part of the input sequence, and assigns weights accordingly using attention mechanisms to grasp global dependencies in the sequence. Experimental evaluations showcase the model's exceptional performance compared to state-of-the-art methods, highlighting its high prediction accuracy. In addressing the challenge of transportation flow estimation, a Spatial-Temporal Graph Convolutional Recurrent Network is proposed. This network learns from both the spatial stations network data and time-series of historical mobility changes to predict urban metro and bike sharing flow at a future time. The model combines Graph Convolutional Networks (GCN) and Long Short-Term Memory (LSTM) Networks to enhance estimation accuracy. Extensive experiments conducted on real-world datasets from the Hangzhou metro system and the NY City bike sharing system validate the effectiveness of the proposed model, showcasing its ability to identify dynamic spatial correlations between stations and make accurate long-term forecasts
Guesdon, Romain. "Estimation de poses humaines par apprentissage profond : application aux passagers des véhicules autonomes". Electronic Thesis or Diss., Lyon 2, 2024. http://www.theses.fr/2024LYO20002.
Pełny tekst źródłaResearch into autonomous cars has made great strides in recent decades, focusing particularly on analysis of the external environment and driving-related tasks. This has led to a significant increase in the autonomy of private vehicles. In this new context, it may be relevant to take an interest in the passengers of these autonomous vehicles, to study their behavior in the face of this revolution in the means of transport. The AURA AutoBehave project has been set up to explore these issues in greater depth. This project brings together several laboratories conducting research in different scientific disciplines linked to this theme, such as computer vision, biomechanics, emotions, and transport economics. This thesis carried out at the LIRIS laboratory is part of this project, in which we focus on methods for estimating the human poses of passengers using deep learning. We first looked at state-of-the-art solutions and developed both a dataset and a metric better suited to the constraints of our context. We also studied the visibility of the keypoints to help estimate the pose. We then tackled the problem of domain generalisation for pose estimation to propose an efficient solution under unknown conditions. Thus, we focused on the generation of synthetic passenger data for pose estimation. Among other things, we studied the application of generative networks and 3D modeling methods to our problem. We have used this data to propose different training strategies and two new network architectures. The proposed fusion approach associated with the training strategies makes it possible to take advantage of both generic and specific datasets, to improve the generalisation capabilities of pose estimation methods inside a car, particularly on the lower body
Shahnaz, Sabina. "Gas flux estimation from surface gas concentrations". Thesis, Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55073.
Pełny tekst źródłaCordova, Vicente D. "Regional-scale carbon flux estimation using MODIS imagery". Virtual Press, 2005. http://liblink.bsu.edu/uhtbin/catkey/1325989.
Pełny tekst źródłaDepartment of Natural Resources and Environmental Management
Goel, Gautam. "Dynamic flux estimation a novel framework for metabolic pathway analysis /". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31769.
Pełny tekst źródłaCommittee Chair: Voit, Eberhard O.; Committee Member: Butera, Robert; Committee Member: Chen, Rachel; Committee Member: Kemp, Melissa; Committee Member: Neves, Ana Rute. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Bonnefous, Odile. "Estimation des vitesses d'écoulement des flux sanguins par échographie ultrasonore". Paris 7, 1986. http://www.theses.fr/1986PA077224.
Pełny tekst źródłaCooper, Daniel Ira. "Estimation of sensible heat flux from remotely sensed surface temperatures". Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185151.
Pełny tekst źródłaComanescu, Mihai. "Flux and speed estimation techniques for sensorless control of induction motors". Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1116338965.
Pełny tekst źródłaTitle from first page of PDF file. Document formatted into pages; contains xv, 109 p.; also includes graphics. Includes bibliographical references (p. 106-109). Available online via OhioLINK's ETD Center
Abareshi, Behzad. "Sensible heat flux estimation over a prairie grassland by neural networks". Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23765.
Pełny tekst źródłaToffa, Ohini Kafui. "Estimation du flux optique en présence d'occultations par une approche TAC". Mémoire, Université de Sherbrooke, 2009. http://savoirs.usherbrooke.ca/handle/11143/4807.
Pełny tekst źródłaKsiążki na temat "Estimation du flux de passagers"
Fried, Jeremy Steven. Forest inventory-based estimation of carbon stocks and flux in California forests in 1990. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2008.
Znajdź pełny tekst źródłaC, Euler H., Vaughan William W i United States. National Aeronautics and Space Administration., red. Statistical technique for intermediate and long-range estimation of 13-month smoothed solar flux and geomagnetic index. [Marshall Space Flight Center], Ala: National Aeronautics and Space Administration, Marshall Space Flight Center, 1996.
Znajdź pełny tekst źródłaSnoussi, Mamma. Nature, estimation et comparaison des flux de matières issus des bassins versants de l'Adour (France), du Sebou, de l'Oum-er-Rbia et du Souss (Maroc): Impact du climat sur les apports fluviatiles à l'océan. Talence, France: Université de Bordeaux I, 1988.
Znajdź pełny tekst źródłaMuhamad, Nauman Malik. Inverse Estimation of Heat Flux and Temperature in 3D Finite Domain. Grin Verlag, 2016.
Znajdź pełny tekst źródłaVaez-Zadeh, Sadegh. Parameter Estimation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198742968.003.0007.
Pełny tekst źródłaVaez-Zadeh, Sadegh. Rotor Position and Speed Estimation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198742968.003.0006.
Pełny tekst źródłaStatistical technique for intermediate and long-range estimation of 13-month smoothed solar flux and geomagnetic index. [Marshall Space Flight Center], Ala: National Aeronautics and Space Administration, Marshall Space Flight Center, 1996.
Znajdź pełny tekst źródłaCzęści książek na temat "Estimation du flux de passagers"
Karlaganis, G., i J. Dettwiler. "Areal Solute flux Estimation: Legal Aspects". W Field-Scale Water and Solute Flux in Soils, 289–94. Basel: Birkhäuser Basel, 1990. http://dx.doi.org/10.1007/978-3-0348-9264-3_27.
Pełny tekst źródłaGoudar, Chetan T., Richard Biener, James M. Piret i Konstantin B. Konstantinov. "Metabolic Flux Estimation in Mammalian Cell Cultures". W Animal Cell Biotechnology, 301–17. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-399-8_14.
Pełny tekst źródłaGoudar, Chetan T., Richard K. Biener, James M. Piret i Konstantin B. Konstantinov. "Metabolic Flux Estimation in Mammalian Cell Cultures". W Animal Cell Biotechnology, 193–209. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-733-4_13.
Pełny tekst źródłaFeng, Yong, Minghao Zhou i Xinghuo Yu. "Sliding-Mode Observer Based Flux Estimation of Induction Motors". W Intelligent Robotics and Applications, 530–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33515-0_52.
Pełny tekst źródłaHolzhütter, Hermann-Georg, i Anke Schwendel. "Estimation of Enzymatic Flux Rates from Kinetic Isotope Experiments". W Modern Trends in Biothermokinetics, 103–7. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2962-0_18.
Pełny tekst źródłaZhang, Tong, Christiaan F. Labuschagne, Karen H. Vousden i Oliver D. K. Maddocks. "Direct Estimation of Metabolic Flux by Heavy Isotope Labeling Simultaneous with Pathway Inhibition: Metabolic Flux Inhibition Assay". W Metabolic Signaling, 109–19. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8769-6_8.
Pełny tekst źródłaAbtew, Wossenu, i Assefa Melesse. "Crop Yield Estimation Using Remote Sensing and Surface Energy Flux Model". W Evaporation and Evapotranspiration, 161–75. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4737-1_11.
Pełny tekst źródłaSadiq, Muhammad Muneef, i Mohammad Asif. "Numerical Estimation of Interfacial Heat Flux Using Inverse Heat Conduction Method". W Proceedings of International Conference in Mechanical and Energy Technology, 577–88. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2647-3_53.
Pełny tekst źródłaKaran, Vijay Kumar, P. R. Thakura i A. N. Thakur. "Adaptive Compensation Algorithm for Flux Estimation of PM BLDC Motor Drives". W Lecture Notes in Electrical Engineering, 795–801. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8234-4_64.
Pełny tekst źródłaSusitra, D., B. Hema Malini i V. Meenakshi. "Estimation of Magnetic Flux Linkage in SRM Using Various Defuzzification Techniques". W Advances in Intelligent Systems and Computing, 11–20. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2674-6_2.
Pełny tekst źródłaStreszczenia konferencji na temat "Estimation du flux de passagers"
Hong, Chungpyo, Yutaka Asako i Koichi Suzuki. "Performance of Parallel-Flow Gas-to-Gas Micro-Double-Tubes-Heat Exchangers". W ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-12430.
Pełny tekst źródłaChen, Jay Chung, i Lai Ah Wong. "Inverse Estimation of Estuary Flux". W Eighth International Conference on Estuarine and Coastal Modeling. Reston, VA: American Society of Civil Engineers, 2004. http://dx.doi.org/10.1061/40734(145)54.
Pełny tekst źródłaYe, Shubo, Qingjun Zhao, Xiaorong Xiang, Guang Xi i Jianzhong Xu. "Modeling for Tip Clearance Effects on Stall-Onset Condition in Transonic Axial Compressors". W ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-57081.
Pełny tekst źródłaFadgyas, M. C., M. V. Pricop, M. L. Niculescu, M. G. Cojocaru i A. Dumitrache. "Fast computational hypersonic heat flux estimation". W INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2017). Author(s), 2018. http://dx.doi.org/10.1063/1.5043974.
Pełny tekst źródłaChrysoulakis, Nektarios, Mattia Marconcini, Jean-Philippe Gastellu-Etchegorry, C. S. B. Grimmong, Christian Feigenwinter, Fredrik Lindberg, Fabio Del Frate i in. "ANthropogenic heat FLUX estimation from Space". W 2017 Joint Urban Remote Sensing Event (JURSE). IEEE, 2017. http://dx.doi.org/10.1109/jurse.2017.7924591.
Pełny tekst źródłaKlammler, H., K. Hatfield, J. Luz, M. Annable, M. Newman, J. Cho, A. Peacock, V. Stucker, J. Ranville i C. Clark. "Water and contaminant flux estimation from multi-layer passive flux meter measurements". W AFM2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/afm120271.
Pełny tekst źródłaStarcic, Antonio, Anita Martincevic i Mario Vasak. "Estimation of disturbance heat flux in buildings". W 2015 IEEE Sensors Applications Symposium (SAS). IEEE, 2015. http://dx.doi.org/10.1109/sas.2015.7133615.
Pełny tekst źródłaAthavale, Apoorva, Kensuke Sasaki, Takashi Kato i Robert D. Lorenz. "Magnetization state estimation in variable-flux PMSMs". W 2017 IEEE International Electric Machines and Drives Conference (IEMDC). IEEE, 2017. http://dx.doi.org/10.1109/iemdc.2017.8002081.
Pełny tekst źródłaCheewoo Lee. "Estimation of flux linkage by analyzing flux paths in a switched reluctance motor". W 2012 IEEE Vehicle Power and Propulsion Conference (VPPC). IEEE, 2012. http://dx.doi.org/10.1109/vppc.2012.6422788.
Pełny tekst źródłaYan, Zhengzhang, Junlei Zhu i Jiahao Chen. "PM Flux Linkage and Offset Voltage Adaptive Flux Estimation in AC Motor Drives". W 2024 IEEE 10th International Power Electronics and Motion Control Conference (IPEMC2024-ECCE Asia). IEEE, 2024. http://dx.doi.org/10.1109/ipemc-ecceasia60879.2024.10567649.
Pełny tekst źródłaRaporty organizacyjne na temat "Estimation du flux de passagers"
Martz, R. L., R. C. Gast i L. J. Tyburski. Monte Carlo next-event point flux estimation for RCP01. Office of Scientific and Technical Information (OSTI), grudzień 1991. http://dx.doi.org/10.2172/10193014.
Pełny tekst źródłaMichael P. Bacon i Roger Francois. Estimation of Particle Flux and Remineralization Rate from Radioactive Disequilibrium. Office of Scientific and Technical Information (OSTI), maj 2004. http://dx.doi.org/10.2172/824247.
Pełny tekst źródłaMcLaughlin, David J. UMass Participation in Air-Sea Flux Estimation in High Wind Boundary Layers. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2001. http://dx.doi.org/10.21236/ada625696.
Pełny tekst źródłaMcLaughlin, David J. UMass Participation in Air-Sea Flux Estimation in High Wind Boundary Layers. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2002. http://dx.doi.org/10.21236/ada627311.
Pełny tekst źródłaFried, Jeremy S., i Xiaoping Zhou. Forest inventory-based estimation of carbon stocks and flux in California forests in 1990. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2008. http://dx.doi.org/10.2737/pnw-gtr-750.
Pełny tekst źródłaKAPLAN, DANIEL. Estimation of Tritium Annual Flux From Concrete Rubble Buried in the E-Area Slit Trenches. Office of Scientific and Technical Information (OSTI), sierpień 2004. http://dx.doi.org/10.2172/835581.
Pełny tekst źródłaFourrier, Marine. Integration of in situ and satellite multi-platform data (estimation of carbon flux for trop. Atlantic). EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d7.6.
Pełny tekst źródłaHughes, J. C., A. F. Henry, D. D. Lanning i J. A. Bernard. An experimental evaluation of the instrumented flux synthesis method for the real-time estimation of reactivity. Final report. Office of Scientific and Technical Information (OSTI), styczeń 1996. http://dx.doi.org/10.2172/167217.
Pełny tekst źródłaLiu, X., Z. Chen i S. E. Grasby. Using shallow temperature measurements to evaluate thermal flux anomalies in the southern Mount Meager volcanic area, British Columbia, Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330009.
Pełny tekst źródłaKamai, Tamir, Gerard Kluitenberg i Alon Ben-Gal. Development of heat-pulse sensors for measuring fluxes of water and solutes under the root zone. United States Department of Agriculture, styczeń 2016. http://dx.doi.org/10.32747/2016.7604288.bard.
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