Prediction of the corrosion rates of subsea pipelines via KPCA by Shiqi Xu, Changhe Huang, Hongda Zhao

“…The model demonstrates effective performance in predicting the corrosion rates of subsea pipelines and offers novel methodologies and concepts for future research in this area.…”
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Various scenarios of measurements using a smartphone with a LiDAR sensor in the context of integration with the TLS point cloud by Janicka Joanna, Błaszczak-Bąk Wioleta

“…In the analysed case, the RMSE registration error was the smallest and amounted to 0.012 m and 0.019 m, while the largest registration error was 0.060 m and 0.065 m, for object 1 and object 2, respectively. …”
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Assessing the effectiveness of long short-term memory and artificial neural network in predicting daily ozone concentrations in Liaocheng City by Qingchun Guo, Zhenfang He, Zhaosheng Wang

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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…Among these, XGBoost demonstrated the highest overall accuracy, achieving an R² value of 0.9926, with low root mean square error (RMSE) and mean absolute error (MAE) of 0.0655 and 0.0191, respectively. …”
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Disentangling Contact Location for Stretchable Tactile Sensors from Soft Waveguide Ultrasonic Scatter Signals by Zhiheng Li, Yuan Lin, Peter B. Shull, Hongliang Ren

“…The experimental results indicate that the accuracy of the proposed FCLS method has a mean absolute error of 0.627 mm and a mean relative error of 3.19%. …”
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Macroeconomic Dynamics in Pakistan: A VAR Model Analysis of GDP, Inflation, Imports, Exports, and Interest Rates by Waseem Khoso, Muhammad Rafique Doudpoto

“…This research explores dynamic relationships between Pakistan's key macroeconomic variables - GDP, inflation, interest rates, imports, and exports - using a Vector Autoregression (VAR) approach to fill significant gaps in understanding Pakistan's distinct economic dynamics. …”
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Harnessing Machine Learning for Predictive Analysis of Crop Resistance to Extreme Weather Conditions by Pan Susovan Kumar, Shivaj Ghorpade Bipin

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Development of DCS SCADA Teaching Module on A Pid-Based Water Level Control Case Using Labview and Factory I/O by Lutfi, Sukriyah Buwarda

“…This course has case study-based learning from the industrial world and involves very expensive instrumentation devices for Real Plant, so a Teaching Module with factory i/o was created. This research aims to develop a DCS SCADA Teaching Module based on the Water Level Control case using Labview and Factory I/O. …”
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Spatial distribution of nutrients to determine soil fertility in mixed farming based on geostatistical Kriging by Hidayat Arismunandar Katili, Sariani Sariani, Ongky Ongky

“…Validation was conducted using absolute mean error (AME) and absolute error of variation (AVE). …”
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Development and Study of Demodulation Techniques for Frequency Manipulated Signals by D. I. Kaplun, V. V. Gulvanskiy, I. I. Kanatov, D. M. Klionskiy, V. F. Lapizkiy, V. I. Bobrovskiy, K. V. Frolov, A. K. Skvortzov

“…The goal of our research is development and study of different demodulation techniques for a frequency shift keyed signals. …”
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MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…The RF model exhibited reliable performance across most locations. The research findings offer a practical method for forecasting groundwater levels. …”
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Development of a Low-Cost pH Meter for Liquid Chemical Fertilizers by Muhittin Yağmur Polat, Abdullah Beyaz, İbrahim Çilingir

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LSTM-Based State-of-Charge Estimation and User Interface Development for Lithium-Ion Battery Management by Abdellah Benallal, Nawal Cheggaga, Amine Hebib, Adrian Ilinca

“…The proposed framework demonstrates superior prediction accuracy, achieving a Mean Square Error (MSE) of 0.0023 and a Mean Absolute Error (MAE) of 0.0043, outperforming traditional estimation methods. …”
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EFL STUDENTS’ PERSPECTIVES ON THE USE OF SMALLTALK2ME TO ENHANCE SPEAKING SKILLS: A STUDY OF UNDERGRADUATE LEARNERS by Fadlan Rambe, Ernita Daulay

“… This research was initiated based on preliminary survey findings that highlighted the challenges faced by EFL students in speaking English, which subsequently guided the researcher’s focus. …”
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Projection the Extreme Temperatures of Iran's Cold Season Using a Multi-Model Hamadi System with Socio-Economic Scenarios of CMIP6 Models. by Muhammad Ahmadi, Mahmud Kamangar

“…The results showed that the error rate of the used Hammadi model has been able to reduce the error of the models used in forecasting to an optimal extent. …”
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Metacognitive Involvement and Critical Thinking in Technical Students in Information Environment by Natalya N. Krylova

“…Metacognitive involvement in activities and critical thinking are the soft skills students require as a basic adaptation resource in information environment at university, in life, and at work. This research explored the correlation between metacognitive involvement and critical thinking which university students of technical specialties used to navigate information environment. …”
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On Predictive Modeling for the Al2O3 Data Using a New Statistical Model and Machine Learning Approach by Mahmoud El-Morshedy, Zahra Almaspoor, Gadde Srinivasa Rao, Muhammad Ilyas, Afrah Al-Bossly

“…The importance of statistical methods in various research fields is modeling the real data and predicting the future behavior of data. …”
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Ground-to-Satellite FSO Communication: Evaluating Modulation Techniques Under Cloud and Turbulence Effects by Mouna Garai, Maha Sliti

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Predicting algorithm of attC site based on combination optimization strategy by Zhendong Liu, Xi Chen, Dongyan Li, Xinrong Lv, Mengying Qin, Ke Bai, Zhiqiang He, Yurong Yang, Xiaofeng Li, Qionghai Dai

“…The algorithm has better portability and higher prediction accuracy compared with the existing advanced algorithms, among which the Pearson correlation coefficient is 0.87, explained variance score is 0.73, root mean square error is 0.006 and mean absolute error is 0.041. …”
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Comparing the Forecast Performance of Advanced Statistical and Machine Learning Techniques Using Huge Big Data: Evidence from Monte Carlo Experiments by Faridoon Khan, Amena Urooj, Saud Ahmed Khan, Abdelaziz Alsubie, Zahra Almaspoor, Sara Muhammadullah

“…Based on the root mean square error and mean absolute error, the PLS-based factor model outperforms the competitor models in terms of forecasting performance.…”
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