Fracture evolution in steel fiber reinforced concrete (SFRC) of tunnel under static and dynamic loading based on DEM-FDM coupling model by Yu Chen, Dongfeng Yu, Yixian Wang, Yanlin Zhao, Hang Lin, Jingjing Meng, Haoliang Wu

“…The model encompasses the concrete matrix, aggregate, interfacial transition zone and steel fibers, taking into account the random shape of the coarse aggregate and the stochastic distribution of steel fibers. It captures microscopic-level interactions among the coarse aggregate, steel fibers, and matrix. …”
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Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors by Ishita Trivedi, Jason Hou, Giacomo Grasso, Kostadin Ivanov, Fausto Franceschini

“…These uncertainties are then propagated through safety analysis, carried out using the MiniSAS code, following the stochastic sampling approach in DAKOTA. An unprotected transient overpower (UTOP) scenario is considered to assess the effect of input uncertainties on safety parameters such as peak fuel and clad temperatures. …”
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Proportional-Switch Adjustment Process-Based Day-by-Day Evolution Model for Mixed Traffic Flow in an Autonomous Driving Environment by Yihao Huang, Han Zhang, Aiwu Kuang

“…First, based on the travel characteristics of CAVs and HDVs, the user group in a connected autonomous driving environment is classified into three categories, each adhering to the system optimal (SO) criterion, the user equilibrium (UE) criterion, or the stochastic user equilibrium (SUE) criterion. Next, the pure HDV traffic capacity BPR (Bureau of Public Roads) function is adapted into a heterogeneous traffic flow travel time function to compute the travel time cost for mixed traffic flow. …”
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Evaluation of the current status and risks of aquatic ecology in the Jialing River Basin based on the characteristics and succession trends of phytoplankton communities by Maojin Huang, Fei Xu, Jia Xia, Xue Yang, Fubin Zhang, Siyao Liu, Tuo Zhang

“…Morphological identification methods, random forest, neutral community model, and modified stochasticity ratio were used to analyze phytoplankton composition, environmental drivers, and community assembly mechanisms. …”
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Dynamic Prediction Research of Silicon Content in Hot Metal Driven by Big Data in Blast Furnace Smelting Process under Hadoop Cloud Platform by Yang Han, Jie Li, Xiao-Lei Yang, Wei-Xing Liu, Yu-Zhu Zhang

“…Secondly, based on the characteristics of stochastic subgradient projection, the execution time of the SVM solver algorithm does not depend on the size of the sample set, and a structured SVM algorithm based on the neighbor propagation algorithm is proposed, and on this basis, a parallel algorithm for solving the covariance matrix of the training set and a parallel algorithm of the tth iteration of the random subgradient projection are designed. …”
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Assessing Pollution with Heavy Metals and Its Impact on Population Health by Youssef Saliba, Alina Bărbulescu

“…In this study, Principal Component Analysis (PCA), Factor Analysis (FA), and t-distributed Stochastic Neighbor Embedding (t-SNE) were utilized for dimensionality reduction and clustering of data series containing the concentration of 10 heavy metals collected at 14 locations. …”
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Measured Rare Voltage Sags and Clusters of Sags: Prediction Models Driven by the Intermittence Indices by G. M. Casolino, M. de Santis, L. Di Stasio, C. Noce, P. Varilone, P. Verde

“…The clusters of sags represent a stochastic process due to their time dependence; the rare satisfy the requirements for a Poisson distribution process. …”
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Expected annual minima from an idealized moving-average drought index by J. H. Stagge, K. Sung, K. Sung, I. F. Munyejuru, M. A. I. Haidar

“…To accomplish this, we derive a stochastic model and use it to simulate 10 <span class="inline-formula">×10⁶</span> years of daily or monthly SPI values in order to determine the distribution of annual exceedance probabilities. …”
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Automatic History Matching for Adjusting Permeability Field of Fractured Basement Reservoir Simulation Model Using Seismic, Well Log, and Production Data by Le Ngoc Son, Nguyen The Duc, Sumihiko Murata, Phan Ngoc Trung

“…Modification of the ANN model is performed using the simultaneous perturbation stochastic approximation (SPSA) algorithm to calibrate transmission coefficients in the ANN model to minimize the discrepancy between the simulated results and observed data. …”
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SOC-Based Simulation of 3D MIMO Mobile-to-Mobile Fading Channels: A Riemann Sum Approach by Carlos A. Gutierrez, Raul A. Fabian-Rodriguez, Francisco R. Castillo-Soria, Cesar A. Azurdia-Meza, Pablo Adasme

“…The other version is inspired by a stochastic approach that enables the non-ergodic simulation of WSS channels and which can be extrapolated to the simulation of non-WSS channels. …”
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Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms by P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits

“…Renewable energy sources (RES) are seen as a means of the fuel and energy complex carbon footprint reduction but the stochastic nature of generation complicates RES integration with electric power systems. …”
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Energy Efficiency of Using Hybrid Heating Points in Conditions of Integration of Electrical and Thermal Networks of Urban Neighborhoods. Part 1. Justification of the Feasibility of... by A. V. Sednin, M. I. Pozdnyakova

“…The paper discusses the circumstances and technical solutions that contribute to the integration of electrical and thermal networks of urban neighborhoods within the framework of a surplus of electricity generating capacities arising from the imbalance in the development of energy generation and consumption, stochastic processes of market economy development, the transfer of energy-intensive industrial production to other countries, the desire to diversify fuel energy resources, passion for the construction of energy sources for alternative energy resources in counterbalance to traditional energy facilities without taking into account all aspects of the interaction of the former with the environment, etc. …”
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Evidence of active subglacial lakes under a slowly moving coastal region of the Antarctic Ice Sheet by J. F. Arthur, C. Shackleton, G. Moholdt, K. Matsuoka, J. van Oostveen

“…Laser altimetry data from ICESat-2 and ICESat (Ice, Cloud, and Land Elevation Satellites) combined with multi-temporal Reference Digital Elevation Model of Antarctica (REMA) strips reveal that these lakes actively fill and drain over periods of several years. Stochastic analyses of subglacial water routing together with visible surface lineations on ice shelves indicate that these lakes discharge meltwater across the grounding line. …”
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Co-optimising frequency-containment services from zero-carbon sources in electricity grids dominated by Renewable Energy Sources by Aimon Mirza Baig, Luis Badesa, Yi Wang, Goran Strbac

“…In this context, the present paper introduces a frequency-security constrained Stochastic Unit Commitment (SUC) model, which simultaneously co-optimises clean services such as inertia from Synchronous Condensers (SCs) and FR from part-loaded RES and Battery Energy Storage System (BESS). …”
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A Throughfall Collection Method Using Mixed Bed Ion Exchange Resin Columns by Mark E. Fenn, Mark A. Poth, Michael J. Arbaugh

“…However, throughfall collection and analysis is labor intensive and expensive because of the large number of replicate collectors needed and because sample collection and chemical analyses are required on a stochastic precipitation event-based schedule. Therefore we developed and tested a throughfall collector system using a mixed bed ion exchange resin column. …”
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A CRITIC-BPNN APPROACH TO FRICTION STIR WELDING PARAMETRIC SELECTION AND PREDICTION USING AA6082-T6 MATERIAL by Mufutau Adeniyi Abolarin, Adeyinka Oluwo, John Rajan, Swaminathan Jose, Sunday Ayoola Oke |, Alexander Iwodi Agada, Ayomide Sunday Ibitoye

“…For further weight determination between the nodes and edges of the neural networks, the Poisson distribution model was introduced. This stochastic-based method was used to calculate the weights at the edges, between the inputs, hidden layers and outputs of the neural network. …”
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Frequency-specific changes in prefrontal activity associated with maladaptive belief updating in volatile environments in euthymic bipolar disorder by Marina Ivanova, Ksenia Germanova, Dmitry S. Petelin, Aynur Ragimova, Grigory Kopytin, Beatrice A. Volel, Vadim V. Nikulin, Maria Herrojo Ruiz

“…Hierarchical Bayesian modelling revealed BD participants anticipated greater environmental volatility, resulting in a more stochastic mapping from beliefs to actions and paralleled by lower win rates and a reduced tendency to repeat rewarded actions than HC. …”
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Skin Lesion Classification Through Test Time Augmentation and Explainable Artificial Intelligence by Loris Cino, Cosimo Distante, Alessandro Martella, Pier Luigi Mazzeo

“…To improve the interpretability of the models’ decision-making processes, techniques such as t-distributed Stochastic Neighbor Embedding (t-SNE) and Gradient-weighted Class Activation Mapping (Grad-CAM) are employed. t-SNE is utilized to visualize the high-dimensional latent features of the CNNs in a two-dimensional space, providing insights into how the models group different skin lesion classes. …”
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Fire return intervals and recruitment affect population growth rate of canopy trees in tall open forest in humid savanna by Patricia A. Werner, Stephanie J. Peacock

“…Minimum fire return intervals of 2–5 years were generally required for λ ≥1 that would allow populations to persist; these were shorter with stochastic year‐to‐year timing of fires and with higher recruitment rates. …”
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Analysis and 3D modelling of percolated conductive networks in nanoparticle-based thin films by Stanislav Haviar, Benedikt Prifling, Tomáš Kozák, Kalyani Shaji, Tereza Košutová, Šimon Kos, Volker Schmidt, Jiří Čapek

“…Using the experimental data, virtual films were generated through a data-driven stochastic 3D microstructure model that is based on a sphere packing algorithm, where the particle size distribution, porosity and vertical density profile are taken into account. …”
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