Exploring Shared Bicycle Travel Patterns from a Multidimensional Spatiotemporal Interaction Perspective Based on Tensor Decomposition: A Case Study of Central Shenzhen Area by Zheng Jixiang, Tao Haiyang, Zhuo Li, Shi Yufei, Bao Han, Huang Runjie

“…Following this, we applied a tensor decomposition model to the spatiotemporal correlation characteristics of bike-sharing data, enhancing our understanding of the spatiotemporal cycling patterns of residents in central Shenzhen. …”
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Pricing basket options using Monte Carlo simulation employing Cholesky decomposition and variance reduction techniques under the 2D stochastic Black–Scholes equation by Youness Saoudi, Khalid Jeaab, Hanaa Hachimi

“…The two-dimensional Black–Scholes model is chosen for its ability to capture complex market dynamics involving correlated assets. …”
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Trends and socioeconomic inequalities of recommended antenatal care services utilization in Ethiopia: A decomposition analysis using Ethiopian nationwide Demographic Health Surveys... by Yawkal Tsega, Abel Endawkie, Gebeyehu Tsega, Asnakew Molla Mekonen, Yeshimebet Ali Dawed, Chad Stecher

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HDF-Net: Hierarchical Dual-Branch Feature Extraction Fusion Network for Infrared and Visible Image Fusion by Yanghang Zhu, Mingsheng Huang, Yaohua Zhu, Jingyu Jiang, Yong Zhang

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Global, regional, national prevalence, mortality, and disability-adjusted life-years of cutaneous squamous cell carcinoma and trend analysis from 1990 to 2021 and prediction to 204... by Chengling Liu, Xingchen Liu, Pengjuan Cao, Xin Li, Haiming Xin, Sailin Zhu

“…For the purpose of creating focused strategies, it is essential to comprehend geographical variations in cSCC prevalence and trends.MethodsThis study utilized data from the 2021 Global Burden of Diseases (GBD) survey to analyze cSCC across 204 countries and territories. …”
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A New Approach to Constraining Properties of Active Galactic Nucleus Host Galaxies by Combining Image and Spectral Energy Distribution Decomposition: Testing upon the MBH–M⋆ Relati... by Haoran Yu, Lulu Fan, Yunkun Han, Weibin Sun, Yihang Zhang, Xuheng Ding, Yongquan Xue

“…Image decomposition allows us to disentangle optical flux into AGN and stellar components, thereby providing additional constraints on the SED models to derive a more refined stellar mass. …”
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Energy-Efficient Islanding Detection Using CEEMDAN and Neural Network Integration in Photovoltaic Distribution System by Sulayman Kujabi, Emmanuel Asuming Frimpong, Francis Boafo Effah

“…This paper proposes an enhanced islanding detection method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a pattern recognition neural network (PANN). …”
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Assessing the Impact of Climate Change on Methane Emissions from Rice Production Systems in Southern India by Boomiraj Kovilpillai, Gayathri Jawahar Jothi, Diogenes L. Antille, Prabu P. Chidambaram, Senani Karunaratne, Arti Bhatia, Mohan Kumar Shanmugam, Musie Rose, Senthilraja Kandasamy, Selvakumar Selvaraj, Mohammed Mainuddin, Guruanand Chandrasekeran, Sangeetha Piriya Ramasamy, Geethalakshmi Vellingiri

“…Experimental data were subsequently used to guide parametrization and validation of the DeNitrification–DeComposition (DNDC) model. The validation of the model showed good agreement between the measured and modeled data, as denoted by the statistical tests performed, which included CRM (0.09), D-index (0.99), RMSE (7.16), EF (0.96), and R² (0.92). …”
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Intelligent partial discharge sensing system for power grid equipment based on Internet of things by FANG Zheng

“…Firstly, the overall framework of the intelligent PD sensing system for power grid equipment is proposed, and the required software and hardware configuration and the selection of PD detection sensors are given; the PD detection process is further designed, and different principles of PD detection are analyzed, the noise of PD is reduced by the discharge signal analysis method of resonance sparse decomposition; the network model of the intelligent partial discharge sensing system for power grid equipment is designed, including sensor nodes, sink nodes and access nodes. …”
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Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…According to the machine learning theory, a short-term prediction method towards trimaran loads is studied by using an optimized data-driven model. …”
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Assessing the stability of indoor farming systems using data outlier detection by Jean Pompeo, Ziwen Yu, Chi Zhang, Songzi Wu, Ying Zhang, Celina Gomez, Melanie Correll

“…Across different trials, the system displayed varying degrees of resistance to cumulative Agr.Ops, with some trials showing increased resilience over time.DiscussionThe alternative decomposition method used effectively identified outliers and provided valuable insights into the functionality of the system under different operational loads. …”
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Synthesis, characterization, pyrolysis and thermokinetic studies of an energetic ionic liquid: 4-amino-1-methyl-1,2,4-triazolium nitrate by Santhosh G, Supriya N, Vijayalakshmi K. P, Deepthi Thomas

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Data Reconstruction Using Smart Sensor Placement by Farnaz Boudaghi, Danial Waleed, Luis A. Duffaut Espinosa

“…To address the uncertainties inherent in spatio-temporal field estimation, a robust data-driven control method is utilized, providing resilience against unpredictable environmental and model changes. …”
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National estimates of mortality of unintentional drowning in China from 1990 to 2021 and its predicted level in the next decade: results from the global burden of disease study 202... by Liuqing You, Jiangmei Liu, Jieming Zhong, Fangrong Fei

“…In addition, we used decomposition analysis to quantify the drivers of changes in unintentional drowning from 1990 to 2021 and we also predicted the mortality of unintentional drowning in the next 10 years based on APC model.ResultsIn 2021, the deaths attributable to unintentional drowning in China were 57554.02 (95% UI: 47463.15~69111.96), corresponding to age-standardized mortality rate (ASMR) of 4.12 (95% UI: 3.39 ~ 4.96) per 100,000 population. …”
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Transmission Tower Tilt State Recognition Based on Parameter Optimization of VMD-SVD and LSTM by Long ZHAO, Guanru WEN, Zhicheng LIU, Peng YUAN, Xinsheng DONG

“…Finally, the LSTM neural network is introduced for feature classification to form a fault diagnosis model. A 110 kV cathead-type tower is used to verify the proposed model, and the results show that the proposed method can achieve an accuracy of 96.68% in identification of tower tilting state. …”
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A Data-Driven Feature Extraction Process of Interleaved DC/DC Converter Due to the Degradation of the Capacitor in the Aircraft Electrical System by Chenguang Zhang, Pengfei Gao, Ming Huang, Wenjie Liu, Weilin Li, Xiaobin Zhang

“…By employing wavelet decomposition and the Hilbert transform method, a highly correlated time–frequency domain feature is obtained. …”
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SVD-GoRank: Recommender System Algorithm Using SVD and Gower’s Ranking by Ilham Saifudin, Triyanna Widiyaningtyas, Ilham Ari Elbaith Zaeni, Afrig Aminuddin

“…One widely used approach is a memory-based model with ranking orientation. Recently, a ranking algorithm that combines user rating values from SVD (Singular Value Decomposition) and user similarity values has been proposed. …”
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Skin Lesion Segmentation in Clinical Images Using Nonnegative Matrix Factorization and Mutual Information by Eliezer Soares Flores, Jacob Scharcanski

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Growth parameters and age estimates of the mouthless crab, Cardisoma crassum Smith, 1870 (Brachyura: Gecarcinidae) from the Montijo Gulf, Pacific coast of Panama by Roberto C. Lombardo

“…From November 2014 to September 2015 and January 2021 to February 2024, a total of 967 crabs were sampled from five mangrove sites within the Montijo Gulf, Pacific coast of Panama. The modal decomposition method was applied to identify age groups, where the best model fit was obtained with eight age classes and the parameters: L ∞ = 91.51 mm, k = 0.24 year-1, and L 1 = 17.14 mm. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This study presents a data-driven approach using the gappy proper orthogonal decomposition (Gappy POD) algorithm, a reduced-order modeling technique, for real-time temperature monitoring of large-scale battery modules. …”
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