Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

“…In this paper, we combine the SAOCOM-1A L-band synthetic-aperture radar (SAR) and the ground-penetrating radar (GPR) data to develop regression models that predict the SSRDC values. The model features are selected with the Boruta wrapper algorithm based on the SAOCOM-1A images after pre-processing, and the SSRDC values at sampling locations within the research area are calculated with the reflected wave method based on the GPR data. …”
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Analysis of Weak Links in the Mechanized Mining of Underground Metal Mines: Insights from Machine Learning and SHAP Explainability Models by Chengye Yang, Keping Zhou, Jielin Li

“…The MPA–XGBoost model demonstrates a high predictive accuracy for PC (<i>R</i>² = 0.958, <i>VAF</i> = 95.981%, <i>MAE</i> = 4.844, <i>RMSE</i> = 7.033). …”
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Development and validation of trigger tools in primary care: A scoping review. by Inge Dhamanti, Elida Zairina, Ida Nurhaida, Salsabila Salsabila, Fitri Yakub

“…The sensitivity, specificity, and positive predictive value (PPV) of the final algorithm were critical in determining the validity of each trigger. …”
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Design of 3D Environment Combining Digital Image Processing Technology and Convolutional Neural Network by Xiaofei Lu, Shouwang Li

“…These results indicate that the proposed CNN module exhibits strong predictive capabilities for point cloud coordinates. …”
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Identifikasi Kelayakan Air Minum Dengan Metode Analisis Komponen Utama Berbasis Entropi by Thommy willay, Jimmy Tjen, Paskalia Kartini, Riyadi Jimmy Iskandar

“…The experiment was conducted with 811 water samples, where 645 samples were used to train the model and the rest for validating the model predictive accuracy. Based on experiments conducted, it is confirmed that the proposed algorithm can determine the potability of drinking water samples from synthetic data sourced from India with an accuracy of over 98% for potable water data and 100% for non-potable water data. …”
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Effective 3C Resource Utilization and Fair Allocation Strategy for Multi-Task Federated Learning by Chaofeng Zhang, Mianxiong Dong, Kaoru Ota

“…This algorithm implements predictive control based on historical records. …”
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Integrating system dynamics and machine learning for environmental impact analysis of building materials in the demolition process by Babatunde Oluwaseun Ajayi, Mayowa Emmanuel Bamisaye, Hugo Miguel Magalhães Macedo, Issara Sereewatthanawut

“…The RF model shows strong predictive accuracy, with R-squared values of 0.9776 to 0.9990 and mean squared errors between 0.0003 and 0.0356. …”
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Constrained Uncertain System Stabilization with Enlargement of Invariant Sets by Walid Hamdi, Wissal Bey, Naceur Benhadj Braiek

“…The proposed approach is based on robust model predictive control (RMPC) and enhanced maximized sets algorithm (EMSA), which are applied to improve the performance of the closed-loop system and achieve less conservative results. …”
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Correcting the Arcjet Thruster Disturbance in GOES‐16 Magnetometer Data by S. Califf, D. Early, M. Grotenhuis, T. M. Loto'aniu, J. Kronenwetter

“…This study presents a correction algorithm that removes the arcjet signal from the magnetometer data. …”
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Collaborative filtering based on nonnegative/binary matrix factorization by Yukino Terui, Yuka Inoue, Yohei Hamakawa, Kosuke Tatsumura, Kazue Kudo, Kazue Kudo

“…Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix factorization techniques such as nonnegative matrix factorization (NMF) are often employed. …”
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Determining Driving Risk Factors from Near-Miss Events in Telematics Data Using Histogram-Based Gradient Boosting Regressors by Shuai Sun, Montserrat Guillen, Ana M. Pérez-Marín, Linglin Ni

“…Near-miss events, which are highly correlated with accidents, are employed as proxies for accident prediction. This research employs histogram-based gradient boosting regressors (HGBRs) for the analysis of telematics data, with comparisons made across datasets from China and Spain. …”
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Multi-Field-Coupled Model and Solution of Active Electronically Scanned Array Antenna Based on Model Reconstruction by Dan Han, Jin Huang, Jinzhu Zhou, Mei Wang, Sen Xu, Haitao Li, Shen Li

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Nonlinear Elasto-Mammography for Characterization of Breast Tissue Properties by Z. G. Wang, Y. Liu, G. Wang, L. Z. Sun

“…The elastic parameters of normal and cancerous breast tissues are identified by minimizing the difference between the measurement and the corresponding computational prediction. An adjoint method is derived to calculate the gradient of the objective function. …”
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Encryption–decryption-based state estimation for nonlinear complex networks subject to coupled perturbation by Peixia Gao, Chaoqing Jia, Aozhan Zhou

“…A novel EDBSE approach is developed such that the upper bounds of prediction error (PE) covariance (PEC) and estimation error (EE) covariance (EEC) can be derived by resolving Riccati-like difference equations and the estimation parameter (EP) is determined by minimizing the trace of the upper bound of EEC. …”
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Screening for MicroRNA combination with engineered exosomes as a new tool against osteosarcoma in elderly patients by Jiyu Han, Jiyu Han, Zitong Zhao, Yanhong Wang, Yanhong Wang, Tao Yu, Daqian Wan, Daqian Wan

“…Next, we used FunRich software to predict the up-stream transcription factors (TFs) of differentially expressed miRNAs (DE-miRNAs). …”
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Fine-scale carbon stocks mapping in the mangrove forests of Tumaco, Colombia using machine learning and remote sensing approaches by Laura Lozano-Arias, Bryan Ernesto Gallego-Pérez, John Josephraj Selvaraj

“…Additionally, spectral indices significantly enhanced the model’s ability to predict aboveground biomass.…”
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Crowd anomaly estimation and detection: A review by A. Hussein, M.W. Raed, A. Al-Shaikhi, M. Mohandes, B. Liu

“…We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. …”
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Deep-Learning and Dynamic Time Warping-Based Approaches for the Diagnosis of Reactor Systems by Hoejun Jeong, Jihyun Kim, Doyun Jung, Jangwoo Kwon

“…The experiment results demonstrate that the size and position of clamping force degradation can be accurately predicted. It is expected that this research will contribute to enhancing the precision and efficiency of internal structure monitoring in nuclear power plants.…”
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Early Detection of Parkinson’s Disease Using AI Techniques and Image Analysis by Marilena Ianculescu, Corina Petean, Virginia Sandulescu, Adriana Alexandru, Ana-Mihaela Vasilevschi

“…Methods: The best approach is selected to be integrated in a neurodegenerative disease management platform called NeuroPredict. The most innovative aspects of the presented approaches are related to the employed feature extraction techniques that convert hand-drawn spirals into a frequency spectra, so that frequency features may be extracted and utilized as inputs for various classification algorithms. …”
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Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model by Victor Fernandez, Virgilio Pérez, Rosa Roig

“…This study presents a comprehensive mobility network model designed to predict and optimize the energy supply for FEVs within smart cities. …”
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