Using Response Surface Methodology to Optimize Edible Coating Formulations to Delay Ripening and Preserve Postharvest Quality of Tomatoes by Robin Tsague Donjio, Jean Aghofack Nguemezi, Mariette Anoumaa, Eugene Tafre Phounzong, Justine Odelonne Kenfack, Théophile Fonkou

“…Results showed that the experimental data could be adequately fitted into a second-order polynomial model with coefficient of determination (R2) ranging from 0.775 to 0.976 for all the variables studied. …”
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Assessment of the Characteristics, Scopes and Limits of the Application of Digital Innovations in the Financial Sector by E. S. Zeleneva

“…At the empirical level, methods of statistical, structural and coefficient analysis are applied. …”
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Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating by N. Radhika, M. Sabarinathan, S. Sivaraman

“…Hyperparameter optimization is performed using the random search technique and is compared with the conventional grid search method. The hybrid ensemble technique demonstrates exceptional predictive performance, achieving a coefficient of determination (R2) of 0.92 with a Root Mean Square Error (RMSE) of 2.01 % and a Mean Absolute Error (MAE) of 1.62 % for porosity prediction, and R2 of 0.94 with the RMSE of 82.03 HV and MAE of 66.42 HV for hardness prediction. …”
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Detection of Adulteration of Panax Notoginseng Powder by Terahertz Technology by Bin Li, Hai Yin, A-kun Yang, Ai-guo Ouyang

“…The feature information of models is extracted by elimination of uninformative variable (UVE) method and successive projection algorithm (SPA); combining with back propagation neural network (BPNN), the UVE-BPNN and SPA-BPNN qualitative models are established, respectively. …”
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A reliability model to predict failure behaviour of overlying strata in groundwater-rich coal mine by Ruirui Li, Xiaowei Hou, Luwang Chen, Yingxin Wang, Fuyou Huang, Lanting Wang

“…Rock strength parameters, including cohesion, internal friction angle, uniaxial tensile strength, and softening coefficient, are treated as random variables to determine the rock failure uncertainty. …”
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Discomfort Intolerance Scale: A Study of Reliability and Validity by Kadir ÖZDEL, Özden YALÇINKAYA ALKAR, İbrahim TAYMUR, M. Hakan TÜRKÇAPAR, Erkut ZAMKI, A. Emre SARGIN

“…In order to determine the criterion validity, Beck Anxiety Inventory (BAI) and State-Trait Anxiety Inventory (STAI) were used. …”
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Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

“…The experimental results show that the proposed model achieves superior performance in one-step-ahead AQI prediction, with a Root Mean Squared Error (RMSE) of 3.445, a Mean Absolute Percentage Error (MAPE) of 4.737%, a Coefficient of Determination (R2) of 0.993, a Mean Absolute Error (MAE) of 2.263, a Percentage Bias (PBIAS) of −0.511%, and a Willmott Index of Agreement (WI) of 0.998, outperforming other baseline models.…”
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PENGARUH PEMBIAYAAN MUDHARABAH BERDASARKAN PSAK NOMOR 105 TERHADAP LABA BERSIH DI BANK MUAMALAT INDONESIA PERIODE 2016-2020 by Melinia Putri, Iwan Setiawan, Mia Lasmi Wardiyah, Mia Lasmi Wardiyah

“…And the data analysis used in this research is descriptive statistical analysis, simple linear regression analysis, correlation analysis, coefficient of determination analysis, and t test analysis. …”
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The Influence of Product Quality and Electronic Word of Mouth on Customer Loyalty in Skincare Products at Sociolla Cirebon by Ristalia Indy, Pebi Yanti Nobu Aq, Yusuf Yusuf, Rahmadi Rahmadi

“…A series of statistical analyses were performed, including validity and reliability assessments, multicollinearity and heteroscedasticity tests, multiple linear regression analysis, partial significance testing (T-test), simultaneous significance testing (F-test), and the coefficient of determination (R²) test. The findings reveal that both product quality and e-WOM exert a significant and positive effect on customer loyalty, with an R² value of 0.943, indicating that these variables account for 94.3% of customer loyalty, while the remaining 5.7% is influenced by other factors. …”
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Forecast of hydrocarbon losses in deposits during the development of gas condensate fields by R. K. Dobrolyubova, E. I. Inyakina, I. I. Krasnov, V. V. Inyakin, A. F. Semenenko

“…The studies performed in the framework of the work by the contact and differential method on the reservoir fluid model (MPF) with imitation of the process of natural depletion of the deposit proved that low condensate content leads to lower losses in the reservoir. …”
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Prediction of Corroded Pipeline Failure Pressure Based on Empirical Knowledge and Machine Learning by Hongbo Liu, Xiangzhao Meng

“…The proposed approach achieves a mean absolute percentage error (MAPE) of 2.52%, a root mean square error (RMSE) of 0.39 MPa, and a coefficient of determination (R²) of 0.9886 on the validation set. …”
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Relationship between occurrence of lahar and hydraulic properties of ashfall covered ground in the Arimura River basin of Sakurajima Volcano, Japan by Hayato Sugawara, Yutaka Gonda

“…The results indicated a trend in which the optimal parameters decrease under conditions of increasing monthly ashfall, and the coefficient of determination was approximately 0.18. …”
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Predicting the Cetane Number of Biodiesel using two AI-Models: the Gradient-based ANN and ANN Optimized by Genetic Algorithm by Hadis Tanha, Fatemeh Bashipour

“…The developed models were compared using statistical criteria such as the coefficient of determination (R2), mean square error (MSE), average absolute relative deviation (AARD), standard deviation (STD) and mean absolute percentage error (MAPE). …”
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Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm-optimized backpropagation neural network. by Yeping Shi, Yunbo Shi, Haodong Niu, Jinzhou Liu, Pengjiao Sun

“…It also outperforms the other models at regression prediction, with smaller absolute, mean absolute, and root mean square errors. Its coefficient of determination (R2) is greater than 0.99, surpassing those of the SVM and RF models. …”
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A deep operator network for Bayesian parameter identification of self-oscillators by Tobias Sugandi, Bayu Dharmaputra, Nicolas Noiray

“…We employ DeepONet as a surrogate model for the operator that maps the first Kramers–Moyal (KM) coefficient to the first and second finite-time KM coefficients. …”
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Study of the Feasibility of Regeneration of Central Worn-Out Textures of Ilam City Based on Urban Smart Growth Approach by pakzad azadkhani, mohammad Salavarzizadeh, Fatemeh Farogh Doost

“…The statistical population of the study includes residents of central worn-out texture of Ilam city (population: 12676 people), 384 of whom are selected as the sample of the study using cluster sampling method. The data collection tool is a researcher-made questionnaire that has been confirmed by face validity and Cronbach’s Alpha coefficient, turning out to be 0.701. …”
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The Study on Impacts of Financial Crowdsourcing of Iranian Football Clubs: A Content Analysis Approach by Mohamad Najmi, Abbas Naghizadeh Baghi, Nasrin Azizian Kohan, Mehrdad Moharramzadeh

“…In this research, to check the validity of the methods of validity, transferability, reliability, and verifiability and to calculate reliability, the process of agreement between coders and determination of Fleiss' kappa coefficient was used.Findings: The benefits of financial crowdsourcing include 90 sub-themes grouped into three main themes: organizational, social, and individual consequences.Originality: In general, crowdfunding, as an innovative and practical approach, can significantly increase financial resources for football clubs. …”
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Analysis of physical properties in white and whole wheat sliced bread using digital image processing by Neiry-Dayán Martínez-Lara, Claudia L. Garzón-Castro, Annamaria Filomena-Ambrosio

“…The Stacked Ensemble model obtained a coefficient of determination (R²) of 0.99 and smaller errors in the a* (1.29) and b* (1.57) coordinates. …”
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Seed vigor testing by low temperature germination in early rice by CAO Dongdong, WU Wei, CHEN Shanyu, QIN Yebo, RUAN Guanhai, LU Min, QIAN Peili, HUANG Yutao

“…Especially, the correlation coefficient between germination percentage at 18℃ after 4 days and FE reached 0.932, revealing a fast and accurate method for measuring the seed vigor at a low temperature. …”
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Validation of a didactic model evaluating the usability, usefulness and acceptability of psychological first aid teaching through simulation by Emeric Saguin, Julia Salomé, Benoît Favodon, Bertrand Lahutte, Frédérique Gignoux-Froment

“…The final model incorporating the 15 criteria showed an R2 coefficient of determination of 0.71 (i.e. 71%, F = 4.91, p < 0.001). …”
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