Extrapolation of cavitation and hydrodynamic pressure in lubricated contacts: a physics-informed neural network approach by Faras Brumand-Poor, Freddy Kokou Azanledji, Nils Plückhahn, Florian Barlog, Lukas Boden, Katharina Schmitz

“…To overcome these experimental and computational limitations, machine learning algorithms offer a promising solution. Physics-informed machine learning (PIML) improves on traditional data-driven models by incorporating physical principles. …”
Get full text

Penerapan Artificial Intelligence pada Non Player Character Menggunakan Algoritma Collision Avoidance System dan Random Number Generator pada Game 2D "Balap Egrang" by Asep Saeful Milak, Eka Wahyu Hidayat, Aldy Putra Aldya

“…The results of this study are Android-based games by applying the Collision Avoidance System Algorithm to make NPCs avoid the Obstacle and Random Number Generator Algorithms to make the Obstacle appear randomly. …”
Get full text

Attention-enhanced optimized deep ensemble network for effective facial emotion recognition by Taimoor Khan, Muhammad Yasir, Chang Choi

“…In recent studies, various algorithms have encountered several challenges such as data scarcity, low-resolution images, and suboptimal performance, particularly in real-time applications. …”
Get full text

Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…Our evaluation focuses on various aspects: torque and flux ripple reduction, speed tracking improvement, switching losses minimization, algorithmic complexity simplification, and sensitivity reduction to parameter variations. …”
Get full text

A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv by Michel Visalli, Ronan Symoneaux, Cécile Mursic, Margaux Touret, Flore Lourtioux, Kipédène Coulibaly, Benjamin Mahieu

“…The dataset can therefore be repurposed to assess and compare the performance of different text mining, natural language processing and sentiment analysis algorithms in both French and English, as well as to drive innovations in AI tools for sensory and consumer research.…”
Get full text

Novel genes involved in vascular dysfunction of the middle temporal gyrus in Alzheimer’s disease: transcriptomics combined with machine learning analysis by Meiling Wang, Aojie He, Yubing Kang, Zhaojun Wang, Yahui He, Kahleong Lim, Chengwu Zhang, Li Lu

“…Finally, combining bulk RNA sequencing data and two machine learning algorithms (least absolute shrinkage and selection operator and random forest), four characteristic Alzheimer’s disease feature genes were identified: somatostatin (SST), protein tyrosine phosphatase non-receptor type 3 (PTPN3), glutinase (GL3), and tropomyosin 3 (PTM3). …”
Get full text

Influence of Duodenal–Jejunal Implantation on Glucose Dynamics: A Pilot Study Using Different Nonlinear Methods by David Cuesta-Frau, Daniel Novák, Vacláv Burda, Daniel Abasolo, Tricia Adjei, Manuel Varela, Borja Vargas, Milos Mraz, Petra Kavalkova, Marek Benes, Martin Haluzik

“…In order to assess the validity of this assumption, we conducted a quantitative analysis based on several nonlinear algorithms (Lempel–Ziv Complexity, Sample Entropy, Permutation Entropy, and modified Permutation Entropy), well suited to the characterization of biomedical time series. …”
Get full text

Control of multi-level quadratic DC-DC boost converter for photovoltaic systems using type-2 fuzzy logic technique-based MPPT approaches by Souheyb Mohammed Belhadj, Bouziane Meliani, Habib Benbouhenni, Sarra Zaidi, Z.M.S. Elbarbary, Mohammed M. Alammer

“…The proposed MPPT-T2FLC addresses key limitations of traditional MPPT methods, including the oscillations near the maximum power point (MPP) in incremental conductance (IC) algorithms and the reduced precision of type-1 fuzzy logic (T1FL) controllers under uncertain environmental conditions. …”
Get full text

A Comparative Study of Machine Learning Techniques for Predicting Mechanical Properties of Fused Deposition Modelling (FDM)-Based 3D-Printed Wood/PLA Biocomposite by Prashant Anerao, Atul Kulkarni, Yashwant Munde, Namrate Kharate

“…Four distinct machine learning algorithms have been selected for predictive modeling: Linear Regression, Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost). …”
Get full text

Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea by Hyunji Sang, Jaeyu Park, Soeun Kim, Myeongcheol Lee, Hojae Lee, Sun-Ho Lee, Dong Keon Yon, Sang Youl Rhee

“…Fifteen variables related to patient profiles were integrated and applied to various ML algorithms, including random forest, support vector, XGBoost, decision tree, and AdaBoost regressors. …”
Get full text

An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features by Junjie Wang, Lei Jiang, Le Zhang, Yaqi Liu, Qihong Yu, Yuheng Bu

“…This model integrates diverse algorithms and incorporates weather factors, while regionalizing characteristics of natural gas usage, thereby achieving accurate forecasts of natural gas purchase volumes. …”
Get full text

Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review by Taseef Hasan Farook, Nafij Bin Jamayet, Johari Yap Abdullah, Mohammad Khursheed Alam

“…The current review did not internally analyze the machine learning models and their respective algorithms, nor consider the confounding variables and factors responsible for shaping the orofacial disorders responsible for eliciting pain.…”
Get full text

Integrated Solution Combining Low-Frequency Forced Oscillation Technique and Continuous Equivital Sensor Monitoring for Assessment of Non-Invasive Ambulatory Respiratory Mechanics by Ghada Ben Othman, Amani R. Ynineb, Erhan Yumuk, Hamed Farbakhsh, Cristina Muresan, Isabela Roxana Birs, Alexandra De Raeve, Cosmin Copot, Clara M. Ionescu, Dana Copot

“…The best-fitting fractional-order models for impedance data were identified using genetic algorithms. This study also explores the correlation between impedance model parameters and EQV data, discussing the potential of AI tools for forecasting respiratory properties. …”
Get full text

A self-configuration framework for balancing services in the fog of things by Edson Mota, Jurandir Barbosa, Gustavo B. Figueiredo, Maycon Peixoto, Cássio Prazeres

“…This service utilizes advanced load-balancing algorithms to ensure the workload is evenly distributed among the available gateways, preventing any single node from becoming a bottleneck for the service distributions. …”
Get full text

Classifying Sunn Pest Damaged and Healthy Wheat Grains Across Different Species with YOLOV8 and Vision Transformers by Melike Çolak, Özgü Özkan, Ali Berkol, Nergis Pervan Akman, Murat Ardıç, Okan Sezer, Nazife Gözde Ayter Arpacıoğlu, Zekiye Budak Başçiftçi, Murat Olgun

“…Over time, the number of researchers focusing on this problem by using various machine learning algorithms and image processing techniques has increased. …”
Get full text

Leveraging machine learning for enhanced reservoir permeability estimation in geothermal hotspots: a case study of the Williston Basin by Abdul-Muaizz Koray, Emmanuel Gyimah, Mohamed Metwally, Hamid Rahnema, Olusegun Tomomewo

“…To enhance accuracy, we initially applied various clustering algorithms, including the density-based spatial clustering of applications with noise (DBSCAN), K-means, K-median, and hierarchical clustering methods, to delineate hydraulic flow units (HFU) within the reservoir using porosity, permeability and water saturation core data. …”
Get full text

Nurse management of minor problems in primary care emergencies: a non-randomized controlled trial by Jordi Estarlich-Corominas, Neus Soler-Abril, Anna Casanellas-Chuecos, Sara Becerra-Corzo, Andrea Sofia Bianco, Pere Torán-Monserrat, Rosa García-Sierra

“…Nurse resolution capacity, after applying algorithms, offered quality care, with fewer prescriptions and good patient satisfaction without increasing the total number of consultations due to the same problem. …”
Get full text

可穿戴设备在卒中风险预测及卒中后管理中的应用进展 Research Progress on the Application of Wearable Devices in Stroke Risk Prediction and Post-Stroke Management... by 吴雅婷1，魏宸铭1，桑振华1，陈乐1，梁怡凡1，武剑1，2，3 (WU Yating1, WEI Chenming1, SANG Zhenhua1, CHEN Le1, LIANG Yifan1, WU Jian1,2,3)

“…By integrating with health management platforms and artificial intelligence algorithms, wearable devices can significantly enhance the accuracy of risk assessment, optimize rehabilitation treatment plans, and thus improve the patients’ outcomes. …”
Get full text

Revolutionizing ESCC prognosis: the efficiency of tumor-infiltrating immune cells (TIIC) signature score by Haixia Wang, Shaowei Ma, Zixin Yang, Ren Niu, Haiyong Zhu, Shujun Li, Shaolin Gao, Zhirong Li, Yanhua Tian

“…Twenty machine learning algorithms were further applied to evaluate the prognostic efficacy of TIIC signature score. …”
Get full text

A novel perspective on survival prediction for AML patients: Integration of machine learning in SEER database applications by Zheng-yi Jia, Maierbiya Abulimiti, Yun Wu, Li-na Ma, Xiao-yu Li, Jie Wang

“…Finally, we used 11 machine learning algorithms to predict the survival rate of AML patients at 1, 2, and 3 years, respectively. …”
Get full text