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Статті в журналах з теми "Numerical Extraction Mechanisms"
Li, Zhao Kun, Hua Mei Bian, Li Juan Shi, and Xiao Tie Niu. "Multiobjective Topology Extraction of the Compliant Mechanisms." Advanced Materials Research 971-973 (June 2014): 1941–48. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1941.
Повний текст джерелаEMOTO, Kazuma, Toshiyuki TSUCHIYA, and Yoshinori TAKAO. "Numerical Investigation of Steady and Transient Ion Beam Extraction Mechanisms for Electrospray Thrusters." TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, AEROSPACE TECHNOLOGY JAPAN 16, no. 2 (2018): 110–15. http://dx.doi.org/10.2322/tastj.16.110.
Повний текст джерелаYang, Junyu, Qianghui Xu, Xuan Kou, Geng Wang, Timan Lei, Yi Wang, Xiaosen Li, and Kai H. Luo. "Three-dimensional pore-scale study of methane hydrate dissociation mechanisms based on micro-CT images." Innovation Energy 1, no. 1 (2024): 100015. http://dx.doi.org/10.59717/j.xinn-energy.2024.100015.
Повний текст джерелаTomaszewska, Anna. "The Influence of Molar Extraction in Mandible on the Bone Remodeling Process under Different Chewing Conditions." Acta Mechanica et Automatica 19, no. 1 (March 1, 2025): 148–52. https://doi.org/10.2478/ama-2025-0017.
Повний текст джерелаNguyen Dang Binh, Thanh, Dung Nguyen Trung, and Duc Hong Ta. "MODELING OF ESSENTIAL OIL EXTRACTION PROCESS: APPLICATION FOR ORANGE, POMELO, AND LEMONGRASS." Vietnam Journal of Science and Technology 56, no. 4A (October 19, 2018): 182. http://dx.doi.org/10.15625/2525-2518/56/4a/12811.
Повний текст джерелаYang, Lei, Haonan Guo, Yu Dai, and Wanheng Chen. "A Method for Complex Question-Answering over Knowledge Graph." Applied Sciences 13, no. 8 (April 18, 2023): 5055. http://dx.doi.org/10.3390/app13085055.
Повний текст джерелаBan, Marko, and Neven Duic. "Adaptation of n-heptane autoignition tabulation for complex chemistry mechanisms." Thermal Science 15, no. 1 (2011): 135–44. http://dx.doi.org/10.2298/tsci100514077b.
Повний текст джерелаIlic, Bojana, and Magdalena Djordjevic. "Understanding mass hierarchy in different energy loss mechanisms through heavy flavor data." EPJ Web of Conferences 276 (2023): 02017. http://dx.doi.org/10.1051/epjconf/202327602017.
Повний текст джерелаHe, Siyuan, Fan Zhang, Weidong Hu, Lei Zhuang, Xingbin Ye, and Guoqiang Zhu. "Investigation of Range Profiles from a Simplified Ship on Rough Sea Surface and Its Multipath Imaging Mechanisms." International Journal of Antennas and Propagation 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/894198.
Повний текст джерелаQiao, Yu, Jie Zhang, Qiangqiang He, Yi Gu, Jun Wu, Lei Zhang, and Chongjun Wang. "Truthful Profit Maximization Mechanisms for Mobile Crowdsourcing." Wireless Communications and Mobile Computing 2022 (January 22, 2022): 1–13. http://dx.doi.org/10.1155/2022/8859905.
Повний текст джерелаДисертації з теми "Numerical Extraction Mechanisms"
Chapalain, Thomas. "Investigating the representation of numerosity in humans and convolutional neural networks using high-variability photorealistic stimuli." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG020.
Повний текст джерелаThe ability to rapidly estimate the number of items in a scene without explicit counting, known as visual number sense, has been the focus of extensive research. Experimental studies and computational models have sought to uncover the mechanisms that enable the human brain to extract numerosity at a glance. Recent advances in imaging techniques, including ultra-high-field functional MRI (fMRI), multivariate pattern analysis, and population receptive field (pRF) modeling, have provided deeper insights into how numerical information is encoded in the brain.These studies have highlighted the involvement of higher-order regions, such as the frontal and parietal cortices, but also lower-level areas, in numerical perception. Most research on numerosity perception has relied on simplified visual stimuli, such as binary dot arrays. While useful, these stimuli fail to capture the complexity of real-world visual environments and present a special case where numerosity is tightly correlated with some low-level statistics of the visual input. This raises questions about ecological validity, and about the extent to which previous findings reflected the discrete number of items per se as opposed to correlated low-level factors. In this thesis, we developed a synthetic photorealistic stimulus dataset to address these limitations, introducing high variability in the characteristics of both objects and scenes while maintaining precise experimental control. This dataset allows for the study of numerosity perception in contexts closer to natural images. Using this new dataset of photorealistic renderings of 3D objects embedded in diverse background scenes, our analyses demonstrated that deep convolutional neural networks (CNNs) optimized for object recognition could encode numerical information with robustness to diverse objects and scenes in distributed activity patterns of their higher convolutional layers. Conversely, untrained networks failed to discriminate numerical content across changes in those other high-level visual properties and mainly encoded low-level summary statistics.These findings suggest that untrained models may not truly encode discrete numerosity and emphasize the importance of using complex stimuli to probe the neural mechanisms of visual number sense. Given the role of CNNs' as models of the ventral visual stream, this research motivates further investigation of how numerical information is represented in the brain beyond commonly studied dorsal-parietal areas. Therefore, in an independent 7T fMRI study, we recorded brain activity of both ventral and dorsal visual pathways while participants viewed and attended to the numerical content of similar synthetic photorealistic stimuli.This experimental paradigm enabled us to disentangle numerical information from correlated visual statistics, allowing for the examination of their distinct contributions to brain activity. Our findings revealed that lateral occipital areas, commonly linked to object recognition, could simultaneously represent numerical and object-related information. Additionally, dorsal parietal regions demonstrated a specialized role in encoding numerical information beyond basic visual features. In contrast, low-level visual statistics primarily influenced early visual and higher-level ventral temporal areas, with minimal impact on higher-order dorsal regions. These findings illustrate a hierarchical organization in visual processing, transitioning from encoding of low-level features to more invariant representations of objects and numerosity in higher-level brain areas. Our work underscores the abstract nature of numerosity representations, advancing our understanding of numerical cognition under more realistic visual conditions
Bylin, Johan. "Best practice of extracting magnetocaloric properties in magnetic simulations." Thesis, Uppsala universitet, Materialteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388356.
Повний текст джерелаЧастини книг з теми "Numerical Extraction Mechanisms"
Schulz, H., C. Schwab, and W. L. Wendland. "An Extraction Technique for Boundary Element Methods." In Notes on Numerical Fluid Mechanics (NNFM), 219–31. Wiesbaden: Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-322-89941-5_18.
Повний текст джерелаBaysal, Kudret, Tobias Schafhitzel, Thomas Ertl, and Ulrich Rist. "Extraction and Visualization of Flow Features." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 305–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01106-1_30.
Повний текст джерелаShen, Lawrence K., and An-Nan Chien. "Numerical Solution and Extraction of Design Parameter Curves for a Nonlinear Dynamic System." In Computational Mechanics ’88, 1168–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-61381-4_310.
Повний текст джерелаChemnitz, Alexander, and Thomas Sattelmayer. "Calculation of the Thermoacoustic Stability of a Main Stage Thrust Chamber Demonstrator." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 235–47. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53847-7_15.
Повний текст джерелаLacroix, Zoé, Arnaud Sahuguet, and Raman Chandrasekar. "Information extraction and database techniques: A user-oriented approach to querying the web." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 289–304. Cham: Springer International Publishing, 1998. http://dx.doi.org/10.1007/bfb0054231.
Повний текст джерелаSend, Wolfgang. "Stroke-Wing Engine with Dual Wings for Extracting Power from an Airstream." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 883–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27279-5_77.
Повний текст джерелаSchollenberger, Michael, and Thorsten Lutz. "Comparison of Different Methods for the Extraction of Airfoil Characteristics of Propeller Blades as Input for Propeller Models in CFD." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 24–34. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79561-0_3.
Повний текст джерелаCarrigan, Tobias D., and James P. Talbot. "Extracting Information from Axle-Box Acceleration: On the Derivation of Rail Roughness Spectra in the Presence of Wheel Roughness." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 286–94. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70289-2_29.
Повний текст джерелаSolazzi, Luigi, and Nicola Pellegrini. "Design and Numerical Study of a 2-DoF Mechanism for Efficient Wave Energy Extraction in Onshore Application." In Proceedings of I4SDG Workshop 2021, 3–11. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87383-7_1.
Повний текст джерелаXie Shejuan, Tian Mingming, Pei Cuixiang, Chen Hong-En, Chen Zhenmao, and Takagi Toshiyuki. "Composite Defects Evaluation Using the Hybrid NDT Methods of PECT and EMAT." In Studies in Applied Electromagnetics and Mechanics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-767-2-139.
Повний текст джерелаТези доповідей конференцій з теми "Numerical Extraction Mechanisms"
Bataee, M., M. C. Chai, Z. Bennour, R. Carter, Z. Hamdi, and A. M. Hassan. "CO2-Driven Geothermal Energy Extraction in the Baram Basin, Sarawak: Insights from Numerical Reservoir Simulations." In SPE Conference at Oman Petroleum & Energy Show. SPE, 2024. http://dx.doi.org/10.2118/218756-ms.
Повний текст джерелаPiya, Cecil, Indraneel Sircar, James D. Van de Ven, and David J. Olinger. "Numerical Modeling of Liquid Piston Gas Compression." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10621.
Повний текст джерелаEremin, M. O., A. Yu Peryshkin, L. D. Pavlova, and V. N. Fryanov. "Numerical assessment of the stability of security pillars during the development of adjacent extraction columns of an inclined seam." In Physical Mesomechanics of Materials. Physical Principles of Multi-Layer Structure Forming and Mechanisms of Non-Linear Behavior. Novosibirsk State University, 2022. http://dx.doi.org/10.25205/978-5-4437-1353-3-173.
Повний текст джерелаMasud, Nahian, and Chris Qin. "Numerical Study on Semi-Active Flapping Hydrofoils for Energy Extraction Using Overset Mesh." In ASME 2024 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2024. https://doi.org/10.1115/imece2024-147330.
Повний текст джерелаEsmaeili, Sajjad, Seyed Emad Siadatifar, Mohammad Mesbah, Brij Maini, and Apostolos Kantzas. "Experimental and Numerical Study of Asphaltene Deposition and Precipitation in the Vapor Extraction Process." In SPE Canadian Energy Technology Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212769-ms.
Повний текст джерелаJian, Wu, Zhou Libo, Jiang Yao, Wang Yun, Yang Qi, Qian Chunjiang, Zhang Cheng, et al. "Experimental and Numerical Investigation on Fracture Propagation Sensitivity Parameters in Deep Coal Seams." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-0917.
Повний текст джерелаSu, Wei, Zhiliang Wang, Miao Li, and Linfang Shen. "The Coupling Mechanisms of Seepage and Heat Transfer in Rock Fractures in Enhanced Geothermal Systems Based on the Lattice Boltzmann Method." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-130931.
Повний текст джерелаMoreira, Debora C., Gherhardt Ribatski, and Satish G. Kandlikar. "Review of Enhancement Techniques With Vapor Extraction During Flow Boiling in Microchannels." In ASME 2020 18th International Conference on Nanochannels, Microchannels, and Minichannels collocated with the ASME 2020 Heat Transfer Summer Conference and the ASME 2020 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/icnmm2020-1068.
Повний текст джерелаLiu, Rui, Xuelin Dong, and Deli Gao. "Numerical Simulation of Enhancing Coalbed Methane Recovery by RF Heating with Small Spacing Well Pattern." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-0087.
Повний текст джерелаDang, Yike, Zheng Yang, Shangtong Yang, and Junlong Shang. "Thermal Damage in Crystalline Rocks: The Role of Heterogeneity in Mechanical Performance and Fracture Mechanisms." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-0106.
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