Iol optic power calculation in patients with eye axial length 24‑28 mm without preceding refractive surgery by K. B. Pershin, N. F. Pashinova, A. Iu. Tsygankov, S. L. Legkih

“…Amount of surgically induced astigmatism was determined by the program SIA Calculator v.2.1.Results. …”
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Human identification via digital palatal scans: a machine learning validation pilot study by Ákos Mikolicz, Botond Simon, Aida Roudgari, Arvin Shahbazi, János Vág

“…These parameters were then input into Fisher’s linear discriminant equations with coefficients determined previously on a training set. …”
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DESIGN OF BAND-PASS FILTERS WITH NON-EQUIRIPPLE FREQUENCY RESPONSES by Evgeniy N. Chervinskiy

“…The calculated parameters are determined as a system of equations solution set. The equations are formed by equating coefficients of variables raised to the same powers in transfer function (TF) expressions of designed and realized filters. …”
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A semi‐automated observation approach to quantify mouse skeletal muscle differentiation using immunohistochemistry by Kenta Shimizu, Yamato Yoshida, Kenshin Iwasa, Yasuyuki Fujii, Ursula M. Jacob, Tilman Fritsch, Ali S. Abdelhameed, Vittorio Calabrese, Naomi Osakabe

“…Correlation between manual and semi‐automated analysis showed a coefficient of determination of 0.7132, indicating a significant reduction in analysis time by approximately 20 times. …”
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Machine Learning-Based Indirect Tip Force Sensing and Estimation for Robotic Uterine Manipulation System by Songphon Namkhun, Apiwat Boonkong, Piroon Kaewfoongrungsi, Kovit Khampitak, Daranee Hormdee

“…Three regression models&#x2014;Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM) networks, and Support Vector Regression (SVR)&#x2014;were evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Coefficient of Determination <inline-formula> <tex-math notation="LaTeX">$(\text {R}^{2})$ </tex-math></inline-formula>. …”
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Different Statistical Modeling to Predict Compressive Strength of High-Strength Concrete Modified with Palm Oil Fuel Ash by Soran Abdrahman Ahmad, Bilal Kamal Mohammed, Serwan Khwrshid Rafiq, Brwa Hama Saeed Hamah Ali, Kawa Omer Fqi

“…The performance of each proposed model was gauged using diverse statistical metrics like the coefficient of determination, mean absolute error, root mean square error, and scatter index to identify the most effective model. …”
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Production risk of organic rice due to climate change in Magelang Regency, Central Java, Indonesia by Istiyanti Eni, Widowati Indah, Al Hasan Thohari

“…Respondents consisted of 75 organic rice farmers selected using simple random sampling methods. The data was taken through interviews based on questionnaires and documentation methods. …”
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Estimation of Uniaxial Compressive Strength and Tensile Strength of Sandstone Based on Point Load by LIU Yongzhi, FANG Qingyao, ZHANG Kun, YAO Huayan, LIU Wu, LIU Guang

“…In rock mechanics and engineering practice, accurate and rapid evaluation of uniaxial compressive strength and tensile strength of rock is important for engineering design and construction safety. Traditional test methods are time-consuming and laborious, and the method of determining uniaxial compressive strength and tensile strength of rock by point load strength index is simple and fast. …”
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The Influence of Promotions, Online Customer Reviews, and Online Customer Ratings on Decisions to Purchase Muslim Clothing Products in E-Commerce Shopee on IKHAC Students by Yuniar Nanda Anggraeni, Diah Syifaul A’yuni

“…In the F test, the independent variables promotion, online customer review, and online customer rating simultaneously have a positive and significant influence on the decision to purchase Muslim clothing products on e-commerce Shopee among IKHAC students. Based on the coefficient of determination value, it shows that 66.4% is influenced by the three factors above. …”
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Prediction of Surface Settlement Induced by Large-Diameter Shield Tunneling Based on Machine-Learning Algorithms by Chao Li, Jinhui Li, Zhongqi Shi, Li Li, Mingxiong Li, Dianqi Jin, Guo Dong

“…Three indicators, mean absolute error (MAE), accuracy (ACC), and coefficient of determination (R2), are selected to evaluate the prediction performance. …”
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Spiking Neural Networks Optimized by Improved Cuckoo Search Algorithm: A Model for Financial Time Series Forecasting by Panke Qin, Yongjie Ding, Ya Li, Bo Ye, Zhenlun Gao, Yaxing Liu, Zhongqi Cai, Haoran Qi

“…Applied to futures market price difference prediction, experimental results demonstrate that ICS-SNN achieves reductions of 13.82% in MAE, 21.27% in MSE, and 15.21% in MAPE, while improving the coefficient of determination (R²) from 0.9790 to 0.9822, compared to the baseline SNN. …”
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Development of a Prediction Model for Specific Fuel Consumption in Rotary Tillage Based on Actual Operation by Seung-Jun Kim, Moon-Kyeong Jang, Seok-Joon Hwang, Won Suk Lee, Ju-Seok Nam

“…The model’s accuracy was analyzed using the coefficient of determination (R²) and root mean square error (RMSE), and it was compared with the ASABE’s fuel consumption prediction model. …”
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Rapid Quantitative Detection of Dye Concentration in Pt/TiO₂ Photocatalytic System Based on RGB Sensing by Cuiyan Han, Ziao Wang, Jiahong Cui, Shuqi Liu, Liu Yang, Yang Fu, Baolin Zhu, Cheng Guo

“…The RGB-based PLS model achieved a coefficient of determination (R²) of 0.961 for the prediction set. …”
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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

“…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. …”
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Variogram modelling optimisation using genetic algorithm and machine learning linear regression: application for Sequential Gaussian Simulations mapping by André William Boroh, Alpha Baster Kenfack Fokem, Martin Luther Mfenjou, Firmin Dimitry Hamat, Fritz Mbounja Besseme

“…The study combines GA and machine learning to optimise variogram parameters, including range, sill, and nugget, by minimising the root mean square error (RMSE) and maximising the coefficient of determination (R2). The experimental variograms were computed and modelled using theoretical models, followed by optimisation via evolutionary algorithms. …”
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Studying the Role of Urban Female Activity in Achieving Sustainable Rural Development in Rural district of Ashaghabad, Neyshabour by Masoomeh Mollanorozi, Seid Eskandar Seidaiy, Nasibe hosseini

“…The sample size was determined 384 by the Cochran formula at 95% confidence interval (T = 1.96). …”
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Pointwise prediction of protein diffusive properties using machine learning by Rasched Haidari, Achillefs N Kapanidis

“…The understanding of cellular mechanisms benefits substantially from accurate determination of protein diffusive properties. Prior work in this field primarily focuses on traditional methods, such as mean square displacements, for calculation of protein diffusion coefficients and biological states. …”
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National market of diagnostic tests and test systems by T. S. Brytanova, A. V. Samko, Ye. H. Knysh

“…In the course of work to determine the level of competition between manufacturers of similar groups of tests and test systems set the coefficient of tension. …”
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Improvement of the Metal Extraction and Removal of Harmful Impurities from Sulfide Ores by Polyoxometalate Oxidizers: Design of Experiments and Industrial Modeling by H. Kadkhodayan, T. Alizadeh

“…Under optimized conditions, the extraction efficiency of zinc, copper, and lead and the removal of toxic heavy metals from sulfide ores were determined as above 85%, 81%, 83%, and 99.9% receptivity.…”
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Optimizing irrigation and nitrogen fertilization for winter wheat using the AquaCrop model and water footprint analysis by JIA Yifan, WANG Hao, HAN Ce, XU Zhenghe, LIU Yuyu

“…【Result】The optimal irrigation schemes were determined based on dual objectives: high yield and irrigation water use efficiency. …”
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