Academic literature on the topic 'Reproducibility of scenario'

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Journal articles on the topic "Reproducibility of scenario"

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Simkus, Andrea, Frank PA Coolen, Tahani Coolen-Maturi, Natasha A. Karp, and Claus Bendtsen. "Statistical reproducibility for pairwise t-tests in pharmaceutical research." Statistical Methods in Medical Research 31, no. 4 (2021): 673–88. http://dx.doi.org/10.1177/09622802211041765.

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This paper investigates statistical reproducibility of the [Formula: see text]-test. We formulate reproducibility as a predictive inference problem and apply the nonparametric predictive inference method. Within our research framework, statistical reproducibility provides inference on the probability that the same test outcome would be reached, if the test were repeated under identical conditions. We present an nonparametric predictive inference algorithm to calculate the reproducibility of the [Formula: see text]-test and then use simulations to explore the reproducibility both under the null
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Fary, Camdon, Dean McKenzie, and Richard de Steiger. "Reproducibility of an Intraoperative Pressure Sensor in Total Knee Replacement." Sensors 21, no. 22 (2021): 7679. http://dx.doi.org/10.3390/s21227679.

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Appropriate soft tissue tension in total knee replacement (TKR) is an important factor for a successful outcome. The purpose of our study was to assess both the reproducibility of a modern intraoperative pressure sensor (IOP) and if a surgeon could unconsciously influence measurement. A consecutive series of 80 TKRs were assessed with an IOP between January 2018 and December 2020. In the first scenario, two blinded sequential measurements in 48 patients were taken; in a second scenario, an initial blinded measurement and a subsequent unblinded measurement in 32 patients were taken while lookin
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Hearn, Jeff. "Sexualities, organizations and organization sexualities: Future scenarios and the impact of socio-technologies (a transnational perspective from the global ‘north’)." Organization 21, no. 3 (2014): 400–420. http://dx.doi.org/10.1177/1350508413519764.

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The article opens by briefly reviewing studies of sexuality in and around organizations from the 1970s. These studies showed considerable theoretical, empirical and conceptual development, as in the concept of organization sexuality. Building on this, the article’s first task is to analyse alternative future scenarios for organization sexualities, by way of changing intersections of gender, sexuality and organizational forms. Possible gendered future scenarios are outlined based on, first, gender equality/inequality and, second, gender similarity/difference between women, men and further gende
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Shu, Lele, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li. "rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment." Geoscientific Model Development 17, no. 2 (2024): 497–527. http://dx.doi.org/10.5194/gmd-17-497-2024.

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Abstract. Hydrological modeling is a crucial component in hydrology research, particularly for projecting future scenarios. However, achieving reproducibility and automation in distributed hydrological modeling research for modeling, simulation, and analysis is challenging. This paper introduces rSHUD v2.0, an innovative, open-source toolkit developed in the R environment to enhance the deployment and analysis of the Simulator for Hydrologic Unstructured Domains (SHUD). The SHUD is an integrated surface–subsurface hydrological model that employs a finite-volume method to simulate hydrological
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Hafizi, Hamed, and Ali Arda Sorman. "Integrating Meteorological Forcing from Ground Observations and MSWX Dataset for Streamflow Prediction under Multiple Parameterization Scenarios." Water 14, no. 17 (2022): 2721. http://dx.doi.org/10.3390/w14172721.

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Precipitation and near-surface air temperatures are significant meteorological forcing for streamflow prediction where most basins are partially or fully data-scarce in many parts of the world. This study aims to evaluate the consistency of MSWXv100-based precipitation, temperatures, and estimated potential evapotranspiration (PET) by direct comparison with observed measurements and by utilizing an independent combination of MSWXv100 dataset and observed data for streamflow prediction under four distinct scenarios considering model parameter and output uncertainties. Initially, the model is ca
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Mazzorana, B., J. Hübl, and S. Fuchs. "Improving risk assessment by defining consistent and reliable system scenarios." Natural Hazards and Earth System Sciences 9, no. 1 (2009): 145–59. http://dx.doi.org/10.5194/nhess-9-145-2009.

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Abstract. During the entire procedure of risk assessment for hydrologic hazards, the selection of consistent and reliable scenarios, constructed in a strictly systematic way, is fundamental for the quality and reproducibility of the results. However, subjective assumptions on relevant impact variables such as sediment transport intensity on the system loading side and weak point response mechanisms repeatedly cause biases in the results, and consequently affect transparency and required quality standards. Furthermore, the system response of mitigation measures to extreme event loadings represe
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Refaee, Turkey, Zohaib Salahuddin, Yousif Widaatalla, et al. "CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features." Journal of Personalized Medicine 12, no. 4 (2022): 553. http://dx.doi.org/10.3390/jpm12040553.

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Handcrafted radiomics features (HRFs) are quantitative features extracted from medical images to decode biological information to improve clinical decision making. Despite the potential of the field, limitations have been identified. The most important identified limitation, currently, is the sensitivity of HRF to variations in image acquisition and reconstruction parameters. In this study, we investigated the use of Reconstruction Kernel Normalization (RKN) and ComBat harmonization to improve the reproducibility of HRFs across scans acquired with different reconstruction kernels. A set of pha
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Tripathi, Veenu, and Stefano Caizzone. "Virtual Validation of In-Flight GNSS Signal Reception during Jamming for Aeronautics Applications." Aerospace 11, no. 3 (2024): 204. http://dx.doi.org/10.3390/aerospace11030204.

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Accurate navigation is a crucial asset for safe aviation operation. The GNSS (Global Navigation Satellite System) is set to play an always more important role in aviation but needs to cope with the risk of interference, possibly causing signal disruption and loss of navigation capability. It is crucial, therefore, to evaluate the impact of interference events on the GNSS system on board an aircraft, in order to plan countermeasures. This is currently obtained through expensive and time-consuming flight measurement campaigns. This paper shows on the other hand, a method developed to create a vi
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Santana-Perez, Idafen, and María S. Pérez-Hernández. "Towards Reproducibility in Scientific Workflows: An Infrastructure-Based Approach." Scientific Programming 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/243180.

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It is commonly agreed that in silico scientific experiments should be executable and repeatable processes. Most of the current approaches for computational experiment conservation and reproducibility have focused so far on two of the main components of the experiment, namely, data and method. In this paper, we propose a new approach that addresses the third cornerstone of experimental reproducibility: the equipment. This work focuses on the equipment of a computational experiment, that is, the set of software and hardware components that are involved in the execution of a scientific workflow.
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Lee, Daeeop, Giha Lee, Seongwon Kim, and Sungho Jung. "Future Runoff Analysis in the Mekong River Basin under a Climate Change Scenario Using Deep Learning." Water 12, no. 6 (2020): 1556. http://dx.doi.org/10.3390/w12061556.

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In establishing adequate climate change policies regarding water resource development and management, the most essential step is performing a rainfall-runoff analysis. To this end, although several physical models have been developed and tested in many studies, they require a complex grid-based parameterization that uses climate, topography, land-use, and geology data to simulate spatiotemporal runoff. Furthermore, physical rainfall-runoff models also suffer from uncertainty originating from insufficient data quality and quantity, unreliable parameters, and imperfect model structures. As an al
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