AI-based algorithms for estimating hydrochar properties in terms of biomass ultimate analysis by Raouf Hassan, Ali sharifzadegan, Alireza Baghban

“…All models were rigorously validated using these statistical metrics, supported by visual evaluations such as cross-validation plots and error distributions. …”
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Content authentication of H.264/AVC video stream based on semi-fragile watermarking by WANG Xiao-jing, YANG Gao-bo, ZHU Ning-bo

“…For the low bit-rate H.264/AVC video stream,a content authentication scheme was proposed by using semi-fragile watermarking.The energy relationship between two groups of DCT blocks in I frame was utilized to generate content based feature code,which was embedded into low-magnitude DCT coefficients by modifying their signs according to their distribution.An error norm function was introduced to keep the bit-rate relatively stable.Moreover,the frame numbers of P frames were embedded into AC coefficients by utilizing the statistical properties of positive and negative signs.Tamper detection was realized by comparing the extracted watermark and reconstructed authentication code.Experimental results demonstrate the effectiveness of the proposed approach.…”
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The Potential of Machine Learning Methods for Separated Turbulent Flow Simulations: Classical Versus Dynamic Methods by Stefan Heinz

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Identifying Non-Functional Requirements From Unconstrained Documents Using Natural Language Processing and Machine Learning Approaches by Qais A. Shreda, Abualsoud A. Hanani

“…We used A dataset of public requirements documents (PURE) that consists of 79 unconstrained requirements documents in different forms. In our approach, features were extracted from the requirement sentences using four different natural language processing methods including statistical and state-of-the-art semantic analysis presented by Google word2vec and bidirectional encoder representations from transformers models. …”
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Associations between Doximity internal medicine residency navigator reputation rank and publicly available metrics by Christopher R. Stephenson, Jayawant N. Mandrekar, Thomas J. Beckman, Christopher M. Wittich

“…Variables included resident demographics, faculty characteristics, and program features. Statistical analyses involved univariable and multivariable linear regression. …”
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Real-Time DTM Generation with Sequential Estimation and OptD Method by Wioleta Błaszczak-Bąk, Waldemar Kamiński, Michał Bednarczyk, Czesław Suchocki, Andrea Masiero

“…The accuracy of the generated DTM was assessed using root mean square error (RMSE) metrics, with values ranging from 0.041 m to 0.121 m, depending on the reduction level. …”
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Ultrasound differential diagnosis of different forms of stomatogenic maxillary sinusitis by S. D. Varzhapetyan

“….), as fractions (percent) and the error of share. Statistical analysis of the absolute values has been determined by Student's method, comparison of share - by xi-square method. …”
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Testing the Temperature-Mortality Nonparametric Function Change with an Application to Chicago Mortality by Hamdy F. F. Mahmoud

“…Intensive simulation studies are conducted to evaluate the permutation-based test and bootstrap procedure based on Type I error and power. The proposed tests are compared with F tests in terms of Type I error and power. …”
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Predictive modeling of rapid glaucoma progression based on systemic data from electronic medical records by Richul Oh, Hyunjoong Kim, Tae-Woo Kim, Eun Ji Lee

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Aerodynamic model identification of supersonic aircraft using Bayesian approach-based Box–Jenkins structure by Muhammad Fawad Mazhar, Muhammad Wasim, Manzar Abbas, Imran Shafi, Jamshed Riaz, Tae-hoon Kim, Imran Ashraf

“…A closer analysis of results has been conducted through statistical techniques like residual analysis, best-fit percentage, fit percentage error, mean squared error, and model order. …”
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Mode Decomposition Bi-Directional Long Short-Term Memory (BiLSTM) Attention Mechanism and Transformer (AMT) Model for Ozone (O₃) Prediction in Johannesburg, South Africa by Israel Edem Agbehadji, Ibidun Christiana Obagbuwa

“…The performance was evaluated statistically with root mean squared error (RMSE), mean absolute error (MAE), and mean square error (MSE). …”
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Monthly 0.05° winter months snow depth dataset for the Northern Hemisphere from 21 CMIP6 models by Shiqiu Lin, Xiaona Chen, Shunlin Liang, Yangxiaoyue Liu, Yu Li, Huan Li

“…To create a high-resolution monthly snow depth dataset tailored for the Northern Hemisphere winter months (NHMSD), this study employed the Delta statistical downscaling method, in conjunction with a spatial feature transfer technique, to refine snow depth data derived from 21 major general circulation models and four shared socioeconomic pathways sourced from the CMIP6 project. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Machine Learning algorithms are widely used in various fields due to their strong capability to extract and display high-level features of training samples. Autoencoder networks show a high ability to identify geochemical anomalies. …”
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Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores by Jose W. Naal-Pech, Leonardo Palemón-Arcos, Youness El Hamzaoui

“…Each model’s predictive performance was assessed over 30 independent runs using mean absolute error, root mean squared error, and coefficient of determination, with statistical differences tested via nonparametric hypothesis testing. …”
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Performance of Plug-In Augmented ChatGPT and Its Ability to Quantify Uncertainty: Simulation Study on the German Medical Board Examination by Julian Madrid, Philipp Diehl, Mischa Selig, Bernd Rolauffs, Felix Patricius Hans, Hans-Jörg Busch, Tobias Scheef, Leo Benning

“…Additionally, we conducted an analysis to assess how the models justify their answers, the accuracy of their responses, and the error structure of their answers. Bootstrapping and CIs were used to evaluate the statistical significance of our findings. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The models were evaluated using comprehensive performance metrics and validated through statistical analysis. Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
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Detail-preserving denoising of CT and MRI images via adaptive clustering and non-local means algorithm by Mohit Sharma, Ayush Dogra, Bhawna Goyal, Anita Gupta, Manob Jyoti Saikia

“…Residual noise in the low-rank matrix is then further suppressed through a coefficient-wise linear minimum mean square error LMMSE estimator in the PCA transform domain. …”
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Peculiarities of forming quality parameters of commercial products of cutting lettuce (<i>Lactuca sativa var. capitata L.</i>) depending on the method of cultivation by Н. В. Лещук, О. Б. Барбан, О. П. Башкатова

“…Purpose. To investigate features of commercial head quality formation in varieties of cutting lettuce (Lactuca sativa var. capitata L.) for different growing methods. …”
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AI-Powered Spectral Imaging for Virtual Pathology Staining by Adam Soker, Maya Almagor, Sabine Mai, Yuval Garini

“…The results demonstrate that PCA-reduced data preserved essential image features while enhancing statistical image quality, as indicated by FID and KID scores, and reducing computational complexity. …”
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Predictive modeling of punchouts in continuously reinforced concrete pavement: a machine learning approach by Ghazi Al-Khateeb, Ali Alnaqbi, Waleed Zeiada

“…Initial exploratory analysis reveals varying distributions among the input features, which serves as the foundation for subsequent analysis. …”
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