Article
Mathematics, Interdisciplinary Applications
Mohammad Zakwan, Majid Niazkar
Summary: The study shows that artificial intelligence models can more accurately estimate infiltration rates and perform well in comparison. Compared to traditional models, ANN and the hybrid MGGP-GRG model can significantly reduce errors and improve the accuracy of infiltration rate predictions.
Article
Computer Science, Information Systems
Zhifei Ding, Jiahao Han, Rongtao Qian, Liming Shen, Siru Chen, Lingxin Yu, Yu Zhu, Richen Liu
Summary: This paper proposes a novel time-varying ensemble data visualization approach based on the Bag-of-Features (BoF) model. The approach extracts local feature patches from ensemble scalar data and identifies feature clusters based on temporal correlations. It preserves geo-spatial information and provides insightful and comprehensive evidence for ensemble simulation data analysis.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Article
Computer Science, Artificial Intelligence
Paris A. Karakasis, Athanasios P. Liavas, Nicholas D. Sidiropoulos, Panagiotis G. Simos, Efrosini Papadaki
Summary: Functional magnetic resonance imaging (fMRI) is widely used for studying the human brain. This study proposes a new fMRI data generating model that takes into account both task-related and resting-state components. Experimental tests show that our method can accurately estimate temporal and spatial components even at low Signal to Noise Ratio (SNR), and outperforms standard procedures based on General Linear Models (GLMs).
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Geosciences, Multidisciplinary
Pinhas Alpert, Haim Shafir, Emily Elhacham
Summary: This study focuses on the correlation between rainfall and aerosols on a local scale, with findings showing the highest negative correlation at a positive lag of around 140-160 minutes. The negative correlation values are suggested to be the result of immediate scavenging and a rise in aerosol concentration after rainfall, influenced by aerosol sources, hygroscopic growth, and transport. The consistent lack of significant correlation at negative lags indicates a weak aerosol effect on precipitation.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Meteorology & Atmospheric Sciences
Gaoyun Wang, Yizhou Zhuang, Rong Fu, Siyu Zhao, Hongqing Wang
Summary: A canonical correlation analysis (CCA) model has been developed to enhance seasonal winter rainfall prediction in California, utilizing predictors such as sea surface temperature (SST), vertically integrated vapor transport (IVT), and geopotential height at 250 hPa (Z250) anomalies. The CCA-based model demonstrates higher prediction skills compared to baseline autoregressive models and dynamic predictions by the North American Multi-Model Ensemble (NMME). This statistical model shows promising results in improving winter rainfall prediction accuracy.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2021)
Article
Environmental Sciences
Linh Nguyen Van, Xuan-Hien Le, Giang V. Nguyen, Minho Yeon, May-Thi Tuyet Do, Giha Lee
Summary: This study compares and evaluates the efficacy of 27 kinetic energy (KE) equations based on rainfall intensity (I-r) with observed data. An exponential KE-I-r equation is proposed for the entire Korean site, and the spatial distribution of its parameter is discussed. The study finds that the power-law equation proposed by Sanchez-Moreno et al. and the exponential equation published by Lee and Won provide the most accurate estimates of KE expenditure and KE content in Sangju City. The suggested KE-I-r equation exhibits a comparable correlation with the observed data for the entire Korean site, with high variance in parameter distribution across geography.
Article
Environmental Studies
Tingchen Wu, Xiao Xie, Haoyu Wu, Haowei Zeng, Xiaoya Zhu
Summary: This paper proposes a time-domain correlation model to study the impact of rainfall on landslide deformation and optimize the monitoring indicator system. By analyzing historical data from specific locations, it was found that different landslide areas have different rainfall-landslide deformation correlations, which can provide early warning for landslides with a lag time.
Article
Computer Science, Artificial Intelligence
Debamita Kumar, Pradipta Maji
Summary: Multimodal data analysis is used for identifying sample categories by incorporating supervised information and capturing the nonlinear correlated structures across different views. The proposed architecture, discriminative deep canonical correlation analysis (D2CCA), combines generative models with the learning objective to improve discriminative ability. The joint representation of multi-view data is learned from maximally correlated subspaces.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Water Resources
Giuseppe Mascaro, Simon Michael Papalexiou, Daniel B. Wright
Summary: This study advances the understanding and modeling of the space-time correlation structure and marginal distribution of short-duration precipitation. The results show significant seasonal differences in the correlation structure and distribution of precipitation, with summer precipitation exhibiting weak correlation and heavy-tailed distribution, and winter precipitation exhibiting strong correlation and light-tailed distribution. Moreover, the study identifies the anisotropy of winter precipitation at long durations, possibly influenced by the motion of frontal storms.
ADVANCES IN WATER RESOURCES
(2023)
Article
Statistics & Probability
Yujia Deng, Xiwei Tang, Annie Qu
Summary: This paper proposes a new tensor learning approach for cancer diagnosis by using pixel-wise correlation information. By establishing a semi-symmetric correlation tensor decomposition method, informative spatial patterns of pixel-wise correlations are effectively captured. The research results show that the proposed method outperforms other competing methods in terms of pattern recognition and prediction accuracy.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Review
Biochemical Research Methods
Jianbo Fu, Ying Zhang, Jin Liu, Xichen Lian, Jing Tang, Feng Zhu
Summary: Individual variations in drug efficacy, side effects, and adverse drug reactions present a challenge in drug research. Pharmacometabonomics aims to understand drug pharmacokinetics and monitor metabolic pathways. This review discusses technological advances, analytical techniques, data processing strategies, and databases in pharmacometabonomics for personalized medicine.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Environmental Sciences
Shan Ning, Yonggang Ge, Shibiao Bai, Chicheng Ma, Yiran Sun
Summary: This study explored the applicability of TRMM, TRMM nonlinear downscaling, and ANUSPLIN (ANU) interpolation of three different types of precipitation data to define regional-scale rainfall-triggered landslide thresholds. The results showed that TRMM downscaled precipitation data had better detection capability for extreme precipitation events compared to the other two methods. The TRMM downscaled threshold was also found to be better than the ANU interpolation. The cumulative effective rainfall of TRMM downscaled data was preferred as the macroscopic critical rainfall-triggered landslide threshold for early warning.
Article
Environmental Sciences
Yizhuo Wen, Aili Yang, Xiangming Kong, Yueyu Su
Summary: A Bayesian-model-averaging Copula (BMAC) approach is proposed for correlation analysis of monthly rainfall and runoff in Xiangxi River watershed, China. The method improves the representation of marginal distribution of hydrological variables and calibrates the joint distributions of rainfall and runoff using Gumbel Copula.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Environmental Sciences
Tommaso Caloiero, Roberto Coscarelli, Gaetano Pellicone
Summary: This study analyzed rainfall data in the southern Italy's Calabria region and found decreasing trends in annual and winter-autumn rainfall, as well as an increasing trend in summer rainfall.
Article
Automation & Control Systems
Bahram Hemmateenejad, Mohammad Mahdi Bordbar, Zahra Shojaeifard
Summary: This article explains the mechanism and methods for data collection, digitalization, preprocessing, and statistical analysis of colorimetric sensor array data. It also evaluates the applications of these methods in the past decade.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2023)
Article
Environmental Sciences
Tesfamichael H. Kebrom, Selamawit Woldesenbet, Haimanote K. Bayabil, Monique Garcia, Ming Gao, Peter Ampim, Ripendra Awal, Ali Fares
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2019)
Article
Environmental Sciences
Ripendra Awal, Ali Fares, Haimanote Bayabil
Article
Environmental Sciences
Ram L. Ray, Ademola Ibironke, Raghava Kommalapati, Ali Fares
Article
Engineering, Environmental
Haimanote K. Bayabil, Ali Fares, Hatim O. Sharif, Dawit T. Ghebreyesus, Hernan A. Moreno
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2019)
Article
Agronomy
Ripendra Awal, Mohammad Safeeq, Farhat Abbas, Samira Fares, Sanjit K. Deb, Amjad Ahmad, Ali Fares
Article
Environmental Sciences
Laura Brewington, Victoria Keener, Alan Mair
Article
Multidisciplinary Sciences
Ram L. Ray, Richard W. Griffin, Ali Fares, Almoutaz Elhassan, Ripendra Awal, Selamawit Woldesenbet, Eric Risch
SCIENTIFIC REPORTS
(2020)
Article
Environmental Sciences
Hamideh Habibi, Ripendra Awal, Ali Fares, Masoud Ghahremannejad
Article
Green & Sustainable Science & Technology
Abdul Ghaffar Khan, Muhammad Imran, Anwar-ul-Hassan Khan, Ali Fares, Jiri Simunek, Tanveer Ul-Haq, Abdulaziz Abdullah Alsahli, Mohammed Nasser Alyemeni, Shafaqat Ali
Summary: The study in Pakistan on maize cultivation under different irrigation techniques showed that the furrow-irrigated raised bed with plastic mulch treatment had the best performance, improving grain yield and water use efficiency. Summer-sown maize in Pakistan has the potential for sustainable production under semiarid and arid climates.
Article
Engineering, Civil
Hamideh Habibi, Ripendra Awal, Ali Fares, Marouane Temimi
Summary: This study aimed to evaluate the accuracy of MRMS system in capturing precipitation data during extreme flood events in Harris County, showing that it reasonably captures precipitation at a 15-minute and 15-km temporal and spatial resolution.
JOURNAL OF HYDROLOGY
(2021)
Article
Green & Sustainable Science & Technology
Ripendra Awal, Almoutaz El Hassan, Farhat Abbas, Ali Fares, Haimanote K. Bayabil, Ram L. Ray, Selamawit Woldesenbet
Summary: The study found that chicken manure released significantly more nutrients compared to dairy manure and Milorganite(TM), while Milorganite(TM) released phosphorus at a slower rate. The type and application rate of the amendments have an impact on the dynamics of nutrient release.
Article
Environmental Sciences
Mohamed Abdelkader, Marouane Temimi, Andreas Colliander, Michael H. Cosh, Vicky R. Kelly, Tarendra Lakhankar, Ali Fares
Summary: This study assessed the temporal variability of SMAP soil moisture retrievals throughout the seasons using in-situ soil moisture observations. The results indicated that SMAP retrievals showed different performance levels in different seasons, with the highest accuracy in September and lower accuracy in March to June. Further enhancement of SMAP retrieval over forest sites is needed based on the findings.
Article
Environmental Sciences
Ripendra Awal, Atikur Rahman, Ali Fares, Hamideh Habibi
Summary: Evapotranspiration is an important part of the hydrologic cycle, and accurately quantifying it is crucial for managing crop water requirements. This study evaluated different empirical equations for estimating evapotranspiration and found that the Hargreaves and Samani equation performed the best.
Article
Water Resources
Ripendra Awal, Hamideh Habibi, Ali Fares, Sanjit Deb
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2020)
Article
Agriculture, Multidisciplinary
Ram L. Ray, Ali Fares, Eric Risch
AGRICULTURAL & ENVIRONMENTAL LETTERS
(2018)