Article
Engineering, Mechanical
Shun Wang, Yongbo Li, Khandaker Noman, Dong Wang, Ke Feng, Zheng Liu, Zichen Deng
Summary: The paper proposes a new entropy measure called cumulate spectrum distribution entropy (CSDEn), which can capture frequency-domain information of fault features. The method is evaluated using synthetic signals and experimental data, showing superior performance in detecting dynamic changes and measuring signal complexity compared to other methods.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Mathematics, Interdisciplinary Applications
Keqiang Dong, Shushu Li, Dan Li
Summary: This paper first introduces the properties of fractional cumulative residual entropy (FCRE), and then extends cumulative residual entropy (CRE) to the case of conditional entropy, proposing fractional conditional cumulative residual entropy (FCCRE) and discussing its properties. The validity of these properties is verified using randomly generated sequences with different distributions. Additionally, the definition of empirical fractional conditional accumulative residual entropy is given, and it is proven that it can be used to approximate FCCRE. Finally, an empirical analysis is conducted on aero-engine gas path data, showing that FCRE and FCCRE can effectively capture complex information in the gas path system.
FRACTAL AND FRACTIONAL
(2022)
Article
Engineering, Aerospace
Elisa Morales, Andrea Bornaccioni, Domenico Quagliarella, Renato Tognaccini
Summary: A robust optimization approach based on conditional value at risk function is presented and applied to a robust transonic aerodynamic design problem in the central section of a Blended Wing-Body configuration. The risk function focuses on aerodynamic characteristics of the airfoil, with computational cost reduction techniques introduced to minimize the costly computation of conditional value at risk.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Article
Mathematics
Marius Giuclea, Costin-Ciprian Popescu
Summary: In this paper, we investigate two generalizations of the Lindley distribution and explore their special properties related to the geometric mean and the cumulative residual entropy. Both properties are of great importance from both theoretical and practical perspectives.
Article
Nanoscience & Nanotechnology
Liu He, Zhongtao Li, Jun Zhang, Fei Peng, Shijun Zhao, Hongyu Chen, Hongge Yan, Tao Yang, Shuhai Chen, Bo Liu, Yi Ma, Zhenggang Wu
Summary: This study investigates the possibility of softening Al13Fe4 through Fe-site multi-principal-element doping. The results show that significant softening can be achieved through binary FeNi, ternary FeNiCo, quaternary FeNiCoCr, and quinary FeNiCoCrMn equiatomic doping. The softening effect is closely related to the weakening of chemical bonds induced by the filling of extra electrons. The findings suggest the potential of using high/medium entropy alloys as transition materials in Al-steel dissimilar metal welding/joining.
SCRIPTA MATERIALIA
(2022)
Article
Mathematics, Applied
H. Abdullah Ali Ahmadini, S. Amal Hassan, N. Ahmed Zaky, S. Shokrya Alshqaq
Summary: This article explores the Bayesian estimation of dynamic cumulative residual entropy for Pareto II distribution, considering non-informative and informative priors, and different loss functions. The simulation study shows that the Bayesian estimate under LINEX loss function is preferable in most situations, and the estimated risks decrease as the value of entropy decreases. The inferential procedure developed in this paper is demonstrated using real data.
Article
Mathematics, Interdisciplinary Applications
Meng Xu, Pengjian Shang, Sheng Zhang
Summary: In this study, a modification of cumulative residual entropy (CRE) called multiscale Renyi cumulative residual distribution entropy (MRCE) is proposed for investigating the complexity of time series. Results show that MRCE has high sensitivity to predetermined parameters and can analyze the complexity of different time series at different scales. Additionally, financial time series in the same region exhibit obvious similarities.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Marine
M. Togneri, I. Masters, I. Fairley
Summary: Acoustic Doppler current profilers are commonly used for measuring tidal currents, but are often affected by wave interference. A study found that wave bias can be detected as a data mode, and proposed a novel analysis technique for assessing turbulence and waves at tidal sites.
Article
Physics, Multidisciplinary
Sudheesh Kumar Kattumannil, E. P. Sreedevi, Narayanaswamy Balakrishnan
Summary: In this paper, a generalized measure of cumulative residual entropy is introduced and its properties are studied. Relationships between different measures of entropy and extropy are established.
Article
Nanoscience & Nanotechnology
Yuxin Li, Yiming Lei, Shuang Zhao, Hao Xiao, Haocheng Liu, Yugang Wang, Yixiu Luo, Jie Zhang, Jingyang Wang, Rodney C. Ewing, Chenxu Wang
Summary: Two high entropy pyrochlores (HEPs), Gd2(Ti0.2Zr0.2Sn0.2Hf0.2Ta0.2)2O7 and Gd2(Ti0.2Zr0.2Sn0.2Hf0.2Nb0.2)2O7, were irradiated with 800 keV Kr2+ ions and observed by in situ transmission electron microscopy (TEM). The order-to-disorder phase transformation from pyrochlore to fluorite structure was observed in these HEPs and Gd2Sn2O7 through selected area electron diffraction (SAED), high angle annular dark field scanning transmission electron microscopy (HAADF-STEM), and energy dispersive spectroscopy (EDS) mapping. Density functional theory (DFT) calculations were used to determine the cation antisite defect (CAD) formation energy and the electron localization function (ELF). Both experimental and calculated results indicate that HEPs have higher resistance to phase transformation and amorphization compared to Gd2Sn2O7.
SCRIPTA MATERIALIA
(2023)
Article
Mathematics, Applied
Abdulhakim A. Al-Babtain, Amal S. Hassan, Ahmed N. Zaky, Ibrahim Elbatal, Mohammed Elgarhy
Summary: This article discusses estimating dynamic cumulative residual Renyi entropy (DCRRE) for Lomax distribution using maximum likelihood and Bayesian methods, and compares the results using Monte Carlo simulations. It is found that DCRRE estimates decrease over time and perform well with increasing sample size, with Bayesian estimates under LINEX loss function being more convenient in most situations. Real data set analysis is conducted for further clarification.
Article
Computer Science, Interdisciplinary Applications
Nicolas Langrene, Xavier Warin
Summary: This article revisits the efficient computation of empirical cumulative distribution functions on large, multivariate datasets, proposing two fast and accurate methods. Additionally, a direct connection between cumulative distribution functions and kernel density estimation is established, paving the way for fast algorithms in multivariate kernel estimation and regression.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2021)
Article
Statistics & Probability
N. Unnikrishnan Nair, S. M. Sunoj, G. Rajesh
Summary: In this work, we explore the properties and applications of the cumulative residual entropy of equilibrium distribution of order n and compare it with Shannon's entropy.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2023)
Article
Computer Science, Artificial Intelligence
Jianhang Zhou, Shaoning Zeng, Bob Zhang
Summary: This paper proposes an approximated self-representation method, which learns the self-representation between the data itself and its projections in different spaces, to achieve better pattern classification results.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
M. S. Shama, Sanku Dey, Emrah Altun, Ahmed Z. Afify
Summary: In this article, the authors introduce a new model called Gamma-Gompertz (GGo) distribution, which outperforms other competing distributions in terms of fit. They explore the properties of the GGo distribution and validate its effectiveness through simulation and real data analysis.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Dan Sandink, Slobodan P. Simonovic, Andre Schardong, Roshan Srivastav
ENVIRONMENTAL MODELLING & SOFTWARE
(2016)
Article
Computer Science, Interdisciplinary Applications
Slobodan P. Simonovic, Andre Schardong, Dan Sandink, Roshan Srivastav
ENVIRONMENTAL MODELLING & SOFTWARE
(2016)
Article
Water Resources
Sarah Irwin, Roshan K. Srivastav, Slobodan P. Simonovic, Donald H. Burn
HYDROLOGICAL SCIENCES JOURNAL
(2017)
Article
Engineering, Civil
Sohom Mandal, Roshan K. Srivastav, Slobodan P. Simonovic
JOURNAL OF HYDROLOGY
(2016)
Article
Engineering, Civil
Roshan Srivastav, K. Srinivasan, K. P. Sudheer
JOURNAL OF HYDROLOGY
(2016)
Article
Meteorology & Atmospheric Sciences
Roshan K. Srivastav, Slobodan P. Simonovic
Article
Engineering, Civil
R. K. Srivastav, K. Srinivasan, K. P. Sudheer
JOURNAL OF HYDROLOGY
(2011)
Article
Engineering, Civil
Roshan K. Srivastav, Andre Schardong, Slobodan P. Simonovic
WATER RESOURCES MANAGEMENT
(2014)
Article
Environmental Sciences
Nikhil Bhatia, Roshan Srivastav, Kasthrirengan Srinivasan
Article
Environmental Sciences
Nikhil Bhatia, Jency M. Sojan, Slobodon Simonovic, Roshan Srivastav
Article
Environmental Sciences
Poonam Wagh, Jency M. Sojan, Sriram J. Babu, Renu Valsala, Suman Bhatia, Roshan Srivastav
Summary: The major lockdown due to the COVID-19 pandemic has impacted global socio-economic development and led to reduced pollution levels. A study on Lake Hussain Sagar using remote sensing techniques found significant improvements in water quality during the 2020 lockdown, with historical variations indicating the lowest pollution levels in 2020.
Article
Engineering, Environmental
Meghana Nagaraj, Roshan Srivastav
Summary: Global warming has increased extreme precipitation, leading to floods, resulting in significant impacts on water infrastructure planning, design, and operations in the Monsoon Asian Region. The study reveals regional differences in extreme precipitation models across MAR, with a high prevalence of non-stationary extreme value models compared to stationary models.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Environmental Sciences
Meghana Nagaraj, Roshan Srivastav
Summary: Large-scale interdependent teleconnections have a significant influence on precipitation variability over India. This study focuses on the spatial multivariate selection of climate indices to identify the relevant factors influencing precipitation. Results show that Nino 4, Nino 1 + 2, Trans Nino Index, AMO, QBO, AO, and NAO have a significant influence on precipitation over India, with variations across different regions.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Jay Chordia, Urmila R. Panikkar, Roshan Srivastav, Riyaaz Uddien Shaik
Summary: This study focuses on quantifying the uncertainty associated with the input sources of watershed models, such as the Digital Elevation Model (DEM), Land Use Land Cover (LULC), and precipitation. The results show that using TRMM as a precipitation source and the USGS DEM provide better predictive performance. Additionally, using an appropriate combination of DEM can improve the model's prediction ability with lower uncertainties.
Article
Computer Science, Interdisciplinary Applications
Jeffrey Wade, Christa Kelleher, Barret L. Kurylyk
Summary: This study developed a physically-based water temperature model coupled with the National Water Model (NWM) to assess the potential for water temperature prediction to be incorporated into the NWM at the continental scale. By evaluating different model configurations of increasing complexity, the study successfully simulated hourly water temperatures in the forested headwaters of H.J. Andrews Experimental Forest in Oregon, USA, providing a basis for integrating water temperature simulation with predictions from the NWM.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaun SH. Kim, Lucy A. Marshall, Justin D. Hughes, Lynn Seo, Julien Lerat, Ashish Sharma, Jai Vaze
Summary: A major challenge in hydrologic modelling is producing reliable uncertainty estimates outside of calibration periods. This research addresses the challenge by improving model structures and error models to more reliably estimate uncertainty. The combination of the RBS model and SPUE produces statistically reliable predictions and shows better matching performance in tests.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Juan Pedro Carbonell-Rivera, Javier Estornell, Luis Angel Ruiz, Pablo Crespo-Peremarch, Jaime Almonacid-Caballer
Summary: This study presents Class3Dp, a software for classifying vegetation species in colored point clouds. The software utilizes geometric, spectral, and neighborhood features along with machine learning methods to classify the point cloud, allowing for the recognition of species composition in an ecosystem.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhi Li, Daniel Caviedes-Voullieme, Ilhan Oezgen-Xian, Simin Jiang, Na Zheng
Summary: The optimal strategy for solving the Richards equation numerically depends on the specific problem, particularly when using GPUs. This study investigates the parallel performance of four numerical schemes on both CPUs and GPUs. The results show that the scaling of Richards solvers on GPUs is influenced by various factors. Compared to CPUs, parallel simulations on GPUs exhibit significant variation in scaling across different code sections, with poorly-scaled components potentially impacting overall performance. Nonetheless, using GPUs can greatly enhance computational speed, especially for large-scale problems.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ludovic Cassan, Leo Pujol, Paul Lonca, Romain Guibert, Helene Roux, Olivier Mercier, Dominique Courret, Sylvain Richard, Pierre Horgue
Summary: Methods and algorithms for measuring stream surface velocities have been continuously developed over the past five years to adapt to specific flow typologies. The free software ANDROMEDE allows easy use and comparison of these methods with image processing capabilities designed for measurements in natural environments and with unmanned aerial vehicles. The validation of the integrated algorithms is presented on three case studies that represent the targeted applications: the study of currents for eco-hydraulics, the measurement of low water flows and the diagnosis of hydraulic structures. The field measurements are in very good agreement with the optical measurements and demonstrate the usefulness of the tool for rapid flow diagnosis for all the intended applications.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Mariia Kozlova, Robert J. Moss, Julian Scott Yeomans, Jef Caers
Summary: This paper introduces a framework for quantitative sensitivity analysis using the SimDec visualization method, and tests its effectiveness on decision-making problems. The framework captures critical information in the presence of heterogeneous effects, and enhances its practicality by introducing a formal definition and classification of heterogeneous effects.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Chad R. Palmer, Denis Valle, Edward V. Camp, Wendy-Lin Bartels, Martha C. Monroe
Summary: Simulation games have been used in natural resource management for education and communication purposes, but not for data collection. This research introduces a new design process which involves stakeholders and emphasizes usability, relevance, and credibility testing criteria. The result is a finalized simulation game for future research.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Tao Wang, Chenming Zhang, Ye Ma, Harald Hofmann, Congrui Li, Zicheng Zhao
Summary: This study used numerical modeling to investigate the formation process of iron curtains under different freshwater and seawater conditions. It was found that Fe(OH)3 accumulates on the freshwater side, while the precipitation is inhibited on the seaward side due to high H+ concentrations. These findings enhance our understanding of iron transformation and distribution in subterranean estuaries.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Grant Hutchings, James Gattiker, Braden Scherting, Rodman R. Linn
Summary: Computational models for understanding and predicting fire in wildland and managed lands are becoming increasingly impactful. This paper addresses the characterization and population of mid-story fuels, which are not easily observable through traditional survey or remote sensing. The authors present a methodology to populate the mid-story using a generative model for fuel placement, which can be calibrated based on limited observation datasets or expert guidance. The connection of terrestrial LiDAR as the observations used to calibrate the generative model is emphasized. Code for the methods in this paper is provided.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Saswata Nandi, Pratiman Patel, Sabyasachi Swain
Summary: IMDLIB is an open-source Python library that simplifies the retrieval and processing of gridded meteorological data from IMD, enhancing data accessibility and facilitating hydro-climatic research and analysis.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Pengfei Wu, Jintao Liu, Meiyan Feng, Hu Liu
Summary: In this paper, a new flow distance algorithm called D infinity-TLI is proposed, which accurately estimates flow distance and width function using a two-segment-distance strategy and triangulation with linear interpolation method. The evaluation results show that D infinity-TLI outperforms existing algorithms and has a low mean absolute relative error.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
