Assessing excavatability in varied rockmass conditions using real-time data and machine learning technique by Shafi Muhammad Pathan, Abdul Ghani Pathan, Muhammad Saad Memon

“…Pareto analysis further highlighted C, UCS, and TS as the most impactful factors, cumulatively accounting for 56% of the total effect on excavation performance. A multiple linear regression model, using TLT as the dependent variable and significant rock properties (C, UCS, M) as predictors, achieved a strong correlation (R=0.76) and explained 76% of the variance, demonstrating the model’s effectiveness in estimating shovel performance. …”
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New Approach for the Calculation of the Intraocular Lens Power Based on the Fictitious Corneal Refractive Index Estimation by Joaquín Fernández, Manuel Rodríguez-Vallejo, Javier Martínez, Ana Tauste, David P. Piñero

“…The SE relative to the intended target was correlated to the difference between real ELP and the value estimated by SRK/T (ΔELP) (r = −0.47, p=0.002), but this only predicted 22% of variability in a linear regression model. The fictitious index for the specular reflection (nk) and Scheimpflug-based devices (nc) were significantly correlated with axial length. …”
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Relationship between Driving Pressure and Mortality in Ventilated Patients with Heart Failure: A Cohort Study by Qilin Yang, Jiezhao Zheng, Xiaohua Chen, Weiyan Chen, Deliang Wen, Xuming Xiong, Zhenhui Zhang

“…We used multivariable logistic regression models, a generalized additive model, and a two-piecewise linear regression model to show the effect of the average driving pressure within 24 h of intensive care unit admission on in-hospital mortality. …”
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The Increasing Financial Impact of Chronic Kidney Disease in Australia by Patrick S. Tucker, Michael I. Kingsley, R. Hugh Morton, Aaron T. Scanlan, Vincent J. Dalbo

“…Prevalence and expenditure predictions were made using a linear regression model. Direct statistical comparisons of rates of annual increase utilised indicator variables in combined regressions. …”
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Credit Risk Management and Profitability of Commercial Banks in Uganda: A Case of Centenary Bank Kabale Branch. by Tushemereirwe, Charity

“…At the bivariate level, a Pearson correlation matrix was conducted to ascertain the relationships between the predictor variables and the dependent variable. A linear regression model was used to fit the data. Research findings from the regression model show that risk identification (r=0.882), risk assessment (r=0.776), and risk controls (r=0.829) had a positive significance on the Centenary Bank Kabale Branch’s profitability. …”
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Performance Appraisal and Employee Performance in Tertiary Institutions: A Study of National Teachers’ Colleges. by Ndagire, Immaculate

“…To determine the associations between the predictor and dependent variables at the bivariate level, a Pearson correlation matrix analysis was carried out. A linear regression model was used to fit the data. Research findings from the regression model show that performance standards (R=862), performance measurement (R=756 and result dissemination (R=829) have a positive significance on the employee’s performance at National Teachers’ Colleges. …”
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Attributable Costs of Postoperative Atrial Fibrillation among Patients Undergoing Cardiac Surgery by Pattamawan Kosuma, Sitichok Wachirasrisirikul, Arom Jedsadayanmata

“…POAF was an independent predictor and increased cost by 23% in linear regression model. On average, patients with POAF had higher medical costs than those without POAF (269,000 versus 218,999 Thai Baht (THB)) with a mean difference of 50,000 THB (1,667 USD). …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…<h4>Conclusions</h4>From 1994 to 2018, under-5 mortality in Bangladesh decreased by 76.72%. While the Linear Regression model demonstrated exceptional accuracy in forecasting trends, long-term predictions should be interpreted cautiously due to inherent uncertainties in socio-economic conditions. …”
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Effects of Oil Drops and the Charcoal’s Proximate Composition on the Air Pollution Emitted from Charcoal Barbecues by Kuo-Pin Yu, Yen-Chi Chen, Yun-Jhe Miao, Sepridawati Siregar, Yu Wei Tsai, Whei-May Grace Lee

“…., CO, CO2, NOx, hydrocarbons (HCs), benzene, toluene, formaldehyde, acetaldehyde, PM2.5, and trace metals (Al, Cr, Cu, Fe, and Zn). A linear regression model was employed to verify the major factors affecting the EFs. …”
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Assessing left main bifurcation anatomy and haemodynamics as a potential surrogate for disease risk in suspected coronary artery disease without stenosis by R. Gharleghi, M. Zhang, C. Shen, M. Webster, C. Ellis, S. Beier

“…We then use a step-down multiple linear regression model to find the best model for predicting lowTAESS, highOSI, highRRT and meanTSVI. …”
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Socioeconomic factors associated with the number of children ever born by married Ghanaian females: a cross-sectional analysis by Felix Boakye Oppong, Divine Darlington Logo, Dennis Boateng, Ephraim Kumi Senkyire

“…Three separate models were considered: linear regression model using CEB and two logistic regression models. …”
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Detailed Compositional and Structure–Property Analysis of Ethylene Oxide‐Propylene Oxide Triblock Copolymers by Gergő Róth, Tibor Nagy, Ákos Kuki, Levente Novák, Dávid Nyul, Miklós Zsuga, Sándor Kéki

“…In addition, a linear regression model has been constructed to find a mathematical relationship between the percentage of ethylene oxide, the average number of propylene oxide units, and the properties of the copolymer.…”
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Association between Healthy Eating Index-2015 total and metabolic associated fatty liver disease in Americans: a cross-sectional study with U.S. National Health and Nutrition Exami... by Genzhong Xu, Ermin Ma, Weitao Zhang, Bo Feng

“…Weighted multivariate linear regression model was performed to assess the linear relationship between the HEI-2015 and MAFLD. …”
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The Role of Organizational Support in Work Engagement Among Nurses Working in Intensive Care Units by Marwa Badwan, Nidal Eshah, Rayan Ahmad

“…Finally, there was a significant positive weak correlation between perceived organizational support and work engagement (r= 0.23, P=0.002). The linear regression model showed that perceived organizational support could predict work engagement (R2 = 0.039). …”
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Educational Intervention of Intention Change for Consumption of Junk Food among School Adolescents in Birgunj Metropolitan City, Nepal, Based on Theory of Planned Behaviors by Upendra Kumar Singh, Nirmal Gautam, Tulsi Ram Bhandari, Nirmal Sapkota

“…Pretest and Posttest group study design and simple random sampling techniques were used. A multiple linear regression model and a paired t-test were used to assess the effectiveness of an educational intervention program. …”
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Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms by Rafael Pires de Lima, Yue Chen, Youzuo Lin

“…Interestingly, the linear regression model is often the most successful when compared to other models, which suggests the relationship between dynamics of trapped 1‐MeV electrons and precipitating electrons is dominated by linear components. …”
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Investigating the Relationship between Traffic Violations and Crashes at Signalized Intersections: An Empirical Study in China by Ze-Hao Jiang, Xiao-Guang Yang, Tuo Sun, Tao Wang, Zheng Yang

“…A White’s test is conducted to test the homoscedasticity of the data and a multiple linear regression model is employed to investigate the relationship between traffic crashes and violations. …”
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Blood Management and Risk Assessment for Transfusion in Pediatric Spinal Deformity Surgery by Pedro Fernandes, Joaquim Soares do Brito, Isabel Flores, Jacinto Monteiro

“…Pearson’s correlation identified patient body weight (r = 0.245, p=0.001) and Cobb angle (r = 0.175, p=0.017) as factors related to blood loss. A linear regression model to estimate hematic losses revealed that only body weight and transfusion showed predictive power, resulting in a low predictive model (R2 = 0.156; F(3,167) = 15.483, p<0.001). …”
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Screens and scars: SEM analysis of the relationship between childhood trauma, emotion regulation, and social media addiction by Nurten Elkin, Ashifa Kariveliparambil Mohammed Ashraf, Oğuzhan Kılınçel, Şenay KılınçeL, Maharshi Ranganathan, Aslıhan Kübra Sakarya, Ayşe Mücella Soydan

“…An analysis of the relationship between social media addiction and childhood trauma revealed that participants with childhood trauma had higher social media addiction. The linear regression model, including childhood traumas and emotion regulation difficulties for social media addiction scores, was statistically significant. …”
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The impact of vaccine access difficulties on HPV vaccine intention and uptake among female university students in China by Weiyi Wang

“…A multivariable logistic regression model and a multiple linear regression model were used to explore factors influencing HPV vaccine uptake and vaccine intention by controlling for potential confounding factors, respectively. …”
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