Improving Data Entry Quality in Enterprise Applications With NLP Methods: A Model Proposal Based on BERT and Deep Learning by H. Canli

“…In this study, a data validation system was developed to improve the accuracy of risk management data collected from an ERP application and to minimize data entry errors. In order to prevent users from incorrectly entering or confusing important data such as Potential Risk, Internal Control, Control and Impact of the Risk during data entry, it is aimed to ensure accurate data entry by using NLP methods. …”
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A Semi‐Analytic Hybrid Approach for Solving the Buckmaster Equation: Application of the Elzaki Projected Differential Transform Method (EPDTM) by Kabir Oluwatobi Idowu, Abdullateef Adedeji, Adedapo Christopher Loyinmi, Guang Lin

“…A detailed comparative analysis of the EPDTM results with exact solutions, using tables, 3D plots, and error graphs, demonstrates the negligible absolute errors achieved by the method. …”
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On the use of kolmogorov–arnold networks for adapting wind numerical weather forecasts with explainability and interpretability: application to madeira international airport by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…Using the Kolmogorov-Arnold Network model led to a substantial reduction in wind speed and direction forecast errors, with a performance that reached a 48.5% improvement to the Global Forecast System 3 h nowcast, considering the mean squared error. …”
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THE PROVISION OF THE INSPECTIONS’ CONTROL ACCURACY ON THE IV, V CATEGORY ROAD BASICS AND COVERINGS BY THE APPLICATION OF H-3 TYPE NIVELIERS by Yu. V. Stolbov, S. Yu. Stolbova, L. A. Pronina, A. I. Uvarov

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Human factors application for healthcare teams in low- and medium-income countries (LMIC) to help improve patient safety and performance by Sukhpreet Singh Dubb, Rachel S. Oeppen, Tomas Svoboda, Peter A. Brennan

“…We can never completely eliminate error, but learning and disseminating lessons from these mistakes to others is essential. …”
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Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing by Jing Tian, Xinyu Chen, Zhennan Liang, Wenliang Qi, Xiaohuan Zheng, Daoli Lu, Bin Chen

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Application of improved P-BEM in time varying channel prediction in 5G high-speed mobile communication system by Hui Yuechao

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Regression machine learning methods for isolation prediction and massive gain broadband MIMO antenna design for 28 GHz applications by Md.Ashraful Haque, Redwan A. Ananta, Jun-Jiat Tiang, Mouaaz Nahas, Md Afzalur Rahman, Narinderjit Singh Sawaran Singh

“…Among the five ML models assessed, Gaussian Process Regression (GPR) showcases the highest accuracy, exhibiting the lowest prediction error in isolation assessments. The results obtained from CST and ADS modeling, alongside actual and expected outcomes from machine learning, indicate that the proposed antenna is a strong candidate for 5G applications.…”
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Regression supervised model techniques THz MIMO antenna for 6G wireless communication and IoT application with isolation prediction by Md. Ashraful Haque, Jamal Hossain Nirob, Kamal Hossain Nahin, Md․ Sharif Ahammed, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Abeer D. Algarni, Mohammed ElAffendi, Ahmed A․ Abd El-Latif, Abdelhamied A. Ateya

“…This article presents unique research on the application of machine learning techniques to enhance the efficiency of antennas for wireless communication and Internet of Things (IoT) applications in the Terahertz (THz) frequency band. …”
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Application of Gradient Boosting Machine Learning Algorithms to Predict Uniaxial Compressive Strength of Soft Sedimentary Rocks at Thar Coalfield by Niaz Muhammad Shahani, Muhammad Kamran, Xigui Zheng, Cancan Liu, Xiaowei Guo

“…According to the results, the XGBoost algorithm outperformed the GBR, Catboost, and LightGBM with coefficient of correlation (R2) = 0.99, mean absolute error (MAE) = 0.00062, mean square error (MSE) = 0.0000006, and root mean square error (RMSE) = 0.00079 in the training phase and R2 = 0.99, MAE = 0.00054, MSE = 0.0000005, and RMSE = 0.00069 in the testing phase. …”
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Haar wavelet Arctic Puffin optimization method (HWAPOM): Application to logistic models with fractal-fractional Caputo-Fabrizio operator by Najeeb Alam Khan, Sahar Altaf, Nadeem Alam Khan, Muhammad Ayaz

“…The accuracy of the designed method was validated by comparing its results with those obtained using the modified Homotopy Perturbation method (MHPM). Error metrics, such as mean absolute error, maximum absolute error, and the experimental convergence rate, are calculated at various collocation points and presented in a tabular format. …”
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Mapping within‑field variability of soybean evapotranspiration and crop coefficient using the Earth Engine Evaporation Flux (EEFlux) application. by Luan Peroni Venancio, Fernando Coelho Eugenio, Roberto Filgueiras, Fernando França da Cunha, Robson Argolo Dos Santos, Wilian Rodrigues Ribeiro, Everardo Chartuni Mantovani

“…The ETa from EEFlux was compared to that of the modified FAO (MFAO) approach using the following statistical metrics: Willmot's index of agreement (d-index), root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). …”
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Study on the application of progressive training method combined with imagery training method in laparoscopic suturing skills training for resident physicians by Wenxue Lin, Jian Yu, Xiaoping Peng, Jianfu Xia, Bingchen Huang, Rizeng Li

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The Application of Near-Infrared Spectroscopy Combined with Chemometrics in the Determination of the Nutrient Composition in Chinese <i>Cyperus esculentus</i> L. by Xiaobo Jiao, Dongliang Guo, Xinjun Zhang, Yunpeng Su, Rong Ma, Lewen Chen, Kun Tian, Jingyu Su, Tangnuer Sahati, Xiahenazi Aierkenjiang, Jingjing Xia, Liqiong Xie

“…The absolute errors between the predicted and actual values for the three-indicator spectral measurements were 0.80, 0.59, and 0.99. …”
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Design and Simulation of Single Input Double Output Coupled Inductor Boost Converter with Bisection Method for Independent Home Application by Indhana Sudiharto, Mochammad Machmud Rifadil, Muhammad Fauzi Romadhoni, Muhamad Milchan

“…The two loads were chosen because they are widely used, aligning with the goal of realizing independent home applications. The simulation test results showed that the voltage output for battery charging in constant voltage mode was 80.6 V, with an error of 0.0515%, and the voltage output for the water circulation pump was 24 V, with an error of 0.33%.…”
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Personalized Prediction of Total Knee Arthroplasty Mechanics Based on Sparse Input Data—Model Validation Using In Vivo Force Data by Sonja Ehreiser, Malte Asseln, Klaus Radermacher

“…<b>Results:</b> The prediction accuracy was quantified using several error metrics, including the root mean square error (RSME). …”
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Identification of Intrinsic Friction and Torque Ripple for a Robotic Joint with Integrated Torque Sensors with Application to Wheel-Bearing Characterization by Sri Harsha Turlapati, Van Pho Nguyen, Juhi Gurnani, Mohammad Zaidi Bin Ariffin, Sreekanth Kana, Alvin Hong Yee Wong, Boon Siew Han, Domenico Campolo

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The application of transfer machine learning to predict and impute missing sulphate levels in different Acid Mine Drainage treatment plants by Taskeen Hasrod, Yannick B. Nuapia, Hlanganani Tutu

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Enhancing IoT-Based Environmental Monitoring and Power Forecasting: A Comparative Analysis of AI Models for Real-Time Applications by Md Minhazur Rahman, Md Ibne Joha, Md Shahriar Nazim, Yeong Min Jang

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Designing an Optimal Model Regarding Early Warning System of Bankruptcy of Banks in Iran Application of Grounded Theory and Econometric Models by Hojjatollah Keshavarz Haddadha, Hamidreza Alipour, Sina Kheradyar

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