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

“…Based upon this research, control laws of supersonic jets have been investigated through a novel technique, further leading to the development of its flight simulator module.…”
Get full text

Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare by Gurdeep Singh

“…It covers performance results rendering research science communication on machine learning models for time series analysis, regression and classification to implement defined and adaptive thresholds, adopting standard deviation and moving average, computing mean square error (MSE), root mean square error (RSME) and mean absolute error (MAE) values, utilizing exponential moving average results on multiple features, prominently targeting resting heartrate data. …”
Get full text

Novel Spatio-Temporal Joint Learning-Based Intelligent Hollowing Detection in Dams for Low-Data Infrared Images by Lili Zhang, Zihan Jin, Yibo Wang, Ziyi Wang, Zeyu Duan, Taoran Qi, Rui Shi

Get full text

A CNN deep learning approach to scour depth estimation around complex bridge piers in steady flow environments by Ngoc Thi Huynh, Anh Thu Thi Phan, Tan Tai Trieu, Ho-Hong-Duy Nguyen, Thanh Nhan Nguyen

“…Results show that the proposed 1D CNN model significantly outperforms traditional approaches, achieving higher coefficient of determination (R 2  = 0.85) values and lower root mean squared error (RMSE = 0.1125), mean absolute error (MAE = 0.1078), and scatter index (SI = 0.1149). …”
Get full text

Physical function evaluation in volleyball training based on intelligent GRNN by Kaiyuan Dong, Borhannudin bin Abdullah, Hazizi bin Abu Saad, Chenxi Lu

“…Comparative experiments conducted on training data of a high-level university men’s volleyball team show that VSGRNN has a goodness-of-fit R2 = 0.927 on the validation set, with a Root Mean Square Error (RMSE) only 1.68 and Symmetric Mean Absolute Percentage Error (SMAPE) controlled at 8.21%. …”
Get full text

Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics by Saima Rashid, Ayesha Siddiqa, Fekadu Tesgera Agama, Nazeran Idrees, Mohammed Shaaf Alharthi

“…The solver’s accuracy is validated by minimal absolute error and complementing responses to every hypothetical situation. …”
Get full text

Towards Real-Time Spatial Distance Monitoring of Power Transmission Lines Using LiDAR Point Clouds and Visual Imaging by Li Zhendong, Wang Feiran, Han Geng, Guo Xinyang, Shi Zhaoyang

“…Spatial distance estimation had a low Mean Absolute Error (MAE) of 0.16 meters and Root Mean Square Error (RMSE) of 0.23 meters. …”
Get full text

Hybrid modeling approaches for predicting COVID-19 mortality: A comparative study across USA, France, and India by B. Uppalaiah, D. Mallikarjuna Reddy, K. Rajalakshmi, P. Vignesh, V. Govindan, Siriluk Donganont

“…Furthermore, we examine the Peak Timing Error and Peak Magnitude Error to ascertain the models' proficiency in capturing essential epidemiological patterns. …”
Get full text

Analysis of Temperature Changes, Vegetation, Evapotranspiration, and Drought Based on Modeling of Landsat 5 and 8 Satellite Imagery and Meteorological Indicators by Mitra Sadat Fathifard, Abbas Rahdan, Mahsa Tohidfar

Get full text

An artificial neural network approach to comparative aspects: A predictive analysis of magnetic dipole on the heat transfer of maxwell hybrid nano coolants flow in an inclined cyli... by J. Aruna, H. Niranjan

“…The ANN accurately predicts performance metrics for inclined and vertical cylinders validated through mean square error (MSE), regression analysis, and error distribution. …”
Get full text

Snowmelt runoff model (SRM) for regulated watersheds with regulation-correction by Ninad Bhagwat, Xiaobing Zhou, Raja Nagisetty, Liping Jiang, Glenn Shaw, Martha Apple, Jeremy Clotfelter

“…The E-SRM framework offers new opportunities for research and practical application in water resource management.…”
Get full text

A novel deep learning approach for investigating liquid fuel injection in combustion system by Syed Azeem Inam, Abdullah Ayub Khan, Noor Ahmed, Tehseen Mazhar, Tariq Shahzad, Sunawar Khan, Mamoon M. Saeed, Habib Hamam

“…The coupled FCNN and Extra Tree Regressor outperform the other algorithms with a Mean Square Error (MSE) of 0.0000005062, Root Mean Square Error (RMSE) of 0.00071148, Mean Absolute Error (MAE) of 0.00020672, and R-squared (R2) value of 0.99998689. …”
Get full text

Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer by J.-S. Chou, H.-M. Nguyen, H.-P. Phan, K.-L. Wang

“…Developing an early warning system for this type of disaster is crucial to reduce its impact on society. This research contributes to developing predictive early warning systems for deep-seated landslide displacement by employing advanced computational models for environmental risk management. …”
Get full text

Analysis of Reaction between α-Lipoic Acid and 2-Chloro-1-methylquinolinium Tetrafluoroborate Used as a Precolumn Derivatization Technique in Chromatographic Determination of α-Lip... by Magdalena Godlewska, Angelika Odachowska, Monika Turkowicz, Joanna Karpinska

Get full text

Effects of internal tides on GNSS-A seafloor crustal deformation observation by Yusuke Yokota, Tadashi Ishikawa, Shun-ichi Watanabe, Koya Nagae, Yuto Nakamura, Eiji Masunaga

“…In future, these results are expected to contribute to progress in multidisciplinary research, such as the construction of advanced physical models and analytical methods.…”
Get full text

Design of Online Electric Power Monitoring For Street Vendors by Endang Sri Rahayu, Puteri Nurul Magfirah, Reza Diharja

“…The objective of this research is to develop an online power monitoring system for street vendors based on RFID sensors and Telegram. …”
Get full text

Bridge Cable Performance Warning Method Based on Temperature and Displacement Monitoring Data by Yan Shi, Yan Wang, Lu-Nan Wang, Wei-Nan Wang, Tao-Yuan Yang

“…Correlation analysis revealed a strong linear correlation between air temperature and quasi-static tower-girder displacements. This research proposes to use the tower-girder distance (effective cable length) to represent the length of the cable, take the thermal expansion coefficient of the effective length of the cable as the quantitative index for long-term monitoring, and take its error as the performance early warning indicator. …”
Get full text

Targeted Data Augmentation for Improving Model Robustness by Mikołajczyk-Bareła Agnieszka, Ferlin Maria, Grochowski Michał

“…By randomly inserting identified biases into training samples, we demonstrated that TDA significantly reduced bias measures by two times to more than 50 times, with only a negligible increase in the error rate. We performed our research on three model families: EfficientNet, DenseNet and Vision Transformer.…”
Get full text

Design and Construction of IoT-Based Overvoltage and Undervoltage Detection Devices by Luki Septya Mahendra, Putu Agus Mahadi Putra, Agus Dinantya Dwi Kurniawan, Hendik Eko Hadi Suharyanto, Lucky Pradigta Setiya Raharja, Yahya Chusna Arif

“…In this research, designed an overvoltage and undervoltage fault detector based on the Internet of Things (IoT), which aims to monitor the quality of electrical voltage in detecting overvoltage / undervoltage faults that change instantly with real-time monitoring. …”
Get full text

Analysis of double side ironless permanent magnet linear synchronous machine with low normal force by Xinghua He, Qixin Sun, Liang Yan, Pengjie Xiang, Tao Zheng

Get full text