Multiscale Modeling of Meandering Fluvial Reservoir Architecture Based on Multiple-Point Geostatistics: A Case Study of the Minghuazhen Formation, Yangerzhuang Oilfield, Bohai Bay... by Jia Li, Chengyan Lin, Xianguo Zhang, Chunmei Dong, Yannan Wei, Wenyan Ning, Changcheng Han, Wei Guo

“…The produced model conforms geologically realistically and enables the prediction of interwell permeability variation to enhance oil recovery.…”
Get full text

Phenology-Aware Machine Learning Framework for Chlorophyll Estimation in Cotton Using Hyperspectral Reflectance by Chunbo Jiang, Yi Cheng, Yongfu Li, Lei Peng, Gangshang Dong, Ning Lai, Qinglong Geng

“…Notably, the optimal prediction accuracy was achieved with fewer than five spectral features. …”
Get full text

Evaluating Security Anomalies by Classifying Traffic Using a Multi-Layered Model by Mohammadreza Samadzadeh, Najmeh Farajipour Ghohroud

Get full text

Perceived worries in the adoption of artificial intelligence among nurses in neonatal intensive care units by Ahmad Ayed, Ahmad Batran, Ibrahim Aqtam, Malakeh Z. Malak, Moath Abu Ejheisheh, Mosaab Farajallah, Lamees Farraj, Sanaa Alkhatib

“…Abstract Introduction Artificial Intelligence (AI) comprises computational algorithms designed to analyze data, learn patterns, and execute tasks traditionally requiring human cognition. …”
Get full text

Problems and perspectives of family doctors training on the undergraduate stage by Yu. M. Kolesnik, V. D. Syvolap, N. S. Mikhaylovskaya, T.O. Kulinich

“…In the educational process teaching materials consist of the work program on the subject, methodological recommendations for independent work and workshops, for practical skills and algorithms for their implementation, tests of initial, current and final knowledge control, samples of basic records of general practice - family medicine, education and qualification characteristics of family doctor, a list of basic regulatory documents, educational literature. …”
Get full text

Empirical Assessment of AI-Powered Tools for Vocabulary Acquisition in EFL Instruction by Yiyun Wang, Jin Wu, Fang Chen, Zhu Wang, Jingjing Li, Liping Wang

“…The findings and conclusions of this study provide valuable insights for EFL educational practice and demonstrate the potential of AI in boosting the effectiveness of language learning, offering empirical support and guidance for future educational decision-making.…”
Get full text

On the Potential of Bayesian Neural Networks for Estimating Chlorophyll-a Concentration from Satellite Data by Mohamad Abed El Rahman Hammoud, Nikolaos Papagiannopoulos, George Krokos, Robert J. W. Brewin, Dionysios E. Raitsos, Omar Knio, Ibrahim Hoteit

“…The performance of the proposed probabilistic model is compared to that of standard ocean color algorithms, namely ocean color 4 (OC4) and ocean color index (OCI). …”
Get full text

A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…Shared control combines human intelligence with autonomous algorithms, demonstrating potential for enhancing the intricate and dynamic operational capabilities of robots. …”
Get full text

Artificial Intelligence Models and Tools for the Assessment of Drug–Herb Interactions by Marios Spanakis, Eleftheria Tzamali, Georgios Tzedakis, Chryssalenia Koumpouzi, Matthew Pediaditis, Aristides Tsatsakis, Vangelis Sakkalis

“…Artificial intelligence (AI) has emerged as a powerful tool in medical sciences that is revolutionizing various fields of drug research. AI algorithms can analyze large-scale biological data and identify molecular targets and pathways advancing pharmacological knowledge. …”
Get full text

Control Theory and Bayesian Networks for Black Spots Study by Leonardo Flores, Jorge Vargas, Alan Ayala, Jeremy Ramos, Edwin Salas

“…To measure the performance and recovery of an urban road network, it is necessary to identify and predict the locations on the network where they occur. …”
Get full text

An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change by J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price

“…The MFSE algorithms were able to effectively leverage the high correlation between each model's predictions of mass change, which all responded similarly to perturbations in the model inputs. …”
Get full text

The RESOLVE and ECO Gas in Galaxy Groups Initiative: The Group Finder and the Group H i–Halo Mass Relation by Zackary L. Hutchens, Sheila J. Kannappan, Andreas A. Berlind, Mehnaaz Asad, Kathleen D. Eckert, David V. Stark, Derrick S. Carr, Ella R. Castelloe, Andrew J. Baker, Kelley M. Hess, Amanda J. Moffett, Mark A. Norris, Darren Croton

“…We present a four-step group-finding algorithm for the Gas in Galaxy Groups (G3) initiative, a spin-off of the z ∼ 0 REsolved Spectroscopy Of a Local VolumE (RESOLVE) and Environmental COntext (ECO) surveys. …”
Get full text

Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism by Lahbib Naimi, El Mahi Bouziane, Lamya Benaddi, Abdeslam Jakimi, Mohamed Manaouch

“…Subsequently, a machine learning algorithm called Bagging was employed to develop a predictive model. …”
Get full text

Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

“…The improved Cauchy mutation grey Wolf optimization algorithm is used to optimize the model training to improve the detection accuracy. …”
Get full text

Interpretable machine learning modeling of temperature rise in a medium voltage switchgear using multiphysics CFD analysis by Mahmood Matin, Amir Dehghanian, Amir Hossein Zeinaddini, Hossein Darijani

“…Artificial intelligence (AI) algorithms have gained attention in various engineering fields to address similar issues. …”
Get full text

Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning by Jian Huang, Lu Wang, Jiangfei Zhou, Tianming Dai, Weicong Zhu, Tianrui Wang, Hongde Wang, Yingze Zhang

“…By comparing the accuracy of the four machine learning models for disease prediction, the SVM model, which includes CEBPB, PTEN, ARPC1B, PIK3R1, and CDC42, was selected. …”
Get full text

Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. …”
Get full text

Digital twin-driven method for determining wind force coefficients of a bridge deck section by Hao-Yang Li, You-Lin Xu, Hai-Li Liao, Lin Huang, Qi Wang

“…The test results collected from the physical model are fused with the virtual model using polynomial regression algorithms to update the virtual model into a digital twin. …”
Get full text

Replicating PET Hydrolytic Activity by Positioning Active Sites with Smaller Synthetic Protein Scaffolds by Yujing Ding, Shanshan Zhang, Xian Kong, Henry Hess, Yifei Zhang

“…Recent breakthroughs in protein structure prediction and de novo design, powered by artificial intelligence, now enable to create enzymes with desired functions without solely relying on traditional genome mining. …”
Get full text

State of Health Estimation of Li-Ion Battery via Incremental Capacity Analysis and Internal Resistance Identification Based on Kolmogorov–Arnold Networks by Jun Peng, Xuan Zhao, Jian Ma, Dean Meng, Shuhai Jia, Kai Zhang, Chenyan Gu, Wenhao Ding

“…Three commonly used machine learning methods (BP, LSTM, TCN) and two hybrid algorithms (LSTM-KAN and TCN-KAN) were used to establish the SOH estimation model. …”
Get full text