A Fusion Method Based on Physical Modes and Satellite Remote Sensing for 3D Ocean State Reconstruction by Yingxiang Hong, Xuan Wang, Bin Wang, Wei Li, Guijun Han

“…This study developed an operational-oriented lightweight framework for three-dimensional ocean state reconstruction by integrating multi-source observations through a computationally efficient multivariate empirical orthogonal function (MEOF) method. …”
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Tomato quality based on colorimetric characteristics of digital images by Thaísa B. Bello, Anderson G. Costa, Thainara R. da Silva, Juliana L. Paes, Marcus V. M. de Oliveira

“…The correlation between colorimetric and physico-chemical variables was analyzed using the Pearson’s coefficient. …”
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Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder by Muzher Saleem, Ghada A. Khouqeer, Fazal Haq, Naglaa AbdelAll, Arshad Hussain, Mohammed Sallah

“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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Empirical Study of the Impact of Unemployment on Political Stability in Iran (1985-2015) by habib samani, robabeh khilkordi

“…Vector regression (VAR), Johansson-Juselius, Vector Error Correction Model (VECM), and variance analysis function were used for this purpose. The results show that in the long run, two variables of unemployment rate and Gini coefficient have a negative and significant relationship with political stability. …”
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Testing the Level of Alternative Institutions as a Slowdown Factor of Economic Development: the Case of Montenegro by Mimo Draškovic, Sanja Bauk, Dalia Streimikiene, Veselin Draskovic

“…On the basis of the conducted statistical examines: standard error of the regression estimate, correlation coefficient, and coefficient of determination are calculated on the basis of previously determined regression coefficients and forecast values of the linear function of free variables (factors: a, b, and c). …”
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Decoding the role of serum cholinesterase among type 2 diabetes mellitus patients at RIMS, Ranchi – A hospital-based study by Avijit Saha, Abha Kumari, Santosh Kumar, Abhay Kumar, Chandrakanta Munni

“…This condition is characterized by variable levels of insulin resistance, impaired insulin secretion, and elevated glucose production. …”
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Association between Oral Health Status and Diabetic Nephropathy-Related Indices in Japanese Middle-Aged Men by Masami Yoshioka, Yoshifumi Okamoto, Masahiro Murata, Makoto Fukui, Shizuko Yanagisawa, Yasuhiko Shirayama, Kojiro Nagai, Daisuke Hinode

“…Logistic regression analysis using eGFR as a dependent variable and age, CPI score, body mass index, HbA1c, and neutral fat as independent variables suggested that low eGFR (<60) could be attributed to CPI score (OR=3.169, 95% CI: 1.031–9.742, p=0.044). …”
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On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

“…The nonlinear differential equations were studied using an original, explicit, and very efficient technique, namely the optimal auxiliary functions method (OAFM). …”
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HEART AND VESSEL REMODELING IN DIFFERENT AGE GROUPS OF PATIENTS WITH ARTERIAL HYPERTENSION by V. N. Kandilova

“…The Spearman rank correlation coefficient (r) was used to estimate the relationship between these variables. …”
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Prediction of Expected Fouling Time During Transmembrane Transition in Reverse Osmosis Systems by Jozsef Lakner, Gabor Lakner

“…However, due to the porous structure of membranes, they are prone to fouling, which reduces their efficiency and can eventually render the membranes incapable of functioning. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Timely identification is crucial for efficient intervention, as untreated diabetic retinopathy can progress to irreversible vision loss. …”
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REVIVAL OF TOURISM DEMAND IN THE POST COVID-19 PANDEMIC PERIOD - A STATISTICAL OVERVIEW IN ROMANIA by Agatha POPESCU, Cristina TINDECHE, Alina MARCUTA, Liviu MARCUTA, Adelaida HONTUS, Mirela STANCIU, Daniela-Mirela PLESOIANU

“…Dynamics of the tourist arrivals and overnight stays involved to establish the trend using polynomial regression functions and determination coefficient. The results showed that the recovery of the tourist flow from its lowest level registered in 2020, the worst year of tourism during the pandemic, needed three years to attain a higher performance than in 2019, a year which was considered the peak in Romania's tourism. …”
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Analyzing Worn-Out Texture Regeneration from Urban Branding Perspective Using Structural Equation Modeling (SEM) (Case Study: Worn-Out Texture of Shahr-e-Kord) by Dvood Mahdavi, Ali Mohammadi Gojani, Waliullah Nazari

“…Furthermore, the findings demonstrated a strong, positive, and significant influence of the branding variable on the regeneration of the worn-out urban fabric with an impact coefficient of 0.833. …”
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On the Global Practical Exponential Stability of <i>h</i>-Manifolds for Impulsive Reaction–Diffusion Cohen–Grossberg Neural Networks with Time-Varying Delays by Gani Stamov, Trayan Stamov, Ivanka Stamova, Cvetelina Spirova

“…The established criteria are less restrictive for the variable domain and diffusion coefficients. The effect of some uncertain parameters on the stability behavior is also considered and a robust practical stability analysis is proposed. …”
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Rapid global fitting of large fluorescence lifetime imaging microscopy datasets. by Sean C Warren, Anca Margineanu, Dominic Alibhai, Douglas J Kelly, Clifford Talbot, Yuriy Alexandrov, Ian Munro, Matilda Katan, Chris Dunsby, Paul M W French

“…This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…Deep SORT is employed for efficient vehicle tracking, while CSRNet facilitates high-density vehicle counting. …”
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The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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Similarity Solutions for Multiterm Time-Fractional Diffusion Equation by A. Elsaid, M. S. Abdel Latif, M. Maneea

“…Based on the obtained results, we propose a definition for a multiterm error function with generalized coefficients.…”
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SMART Based Multi-Point Matching Assisted Approximation of Renewable Interconnected Power System by Umesh Kumar Yadav, V. P. Singh, Luigi Fortuna, Umesh Kumar Sahu

“…For the error minimization, objective function is framed. The objective function is then converted in the form of weighted objective function by employing SMART based weight determination approach. …”
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