Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

“…Consequently, the new pattern, PSLG, was selected for predicting MRI behavior.…”
Get full text

Relationship of Community Mobility, Vital Space, and Faller Status in Older Adults by Diego Robles Cruz, Andrea Lira Belmar, Anthony Fleury, Méline Lam, Rossana M. Castro Andrade, Sebastián Puebla Quiñones, Carla Taramasco Toro

Get full text

The Dynamics Affecting the Export-Import Ratio in Turkey: A Hybrid Model Proposal with Econometrics and Machine Learning Approach by Erdemalp Özden

“…In addition, a 1% increase in consumer price index will increase ratio of exports to imports by 1.9 points, while a 1% increase in producer price index will cause a -0.8 point decrease on the ratio of exports to imports. Then, the pattern between the variables was analyzed with quadratic support vector machine, a machine learning method. …”
Get full text

Machine Learning-Driven Parametric Analysis of Eco-Friendly Ultrasonic Welding for AL6061-CU Alloy Joints by A. Karan, S. Arungalai Vendan, M. R. Nagaraj, M. Chaturvedi, S. Sivadharmaraj

“…The primary focus is on the metallurgical transformations to evaluate the pattern of molecular diffusion and spread within the weld, the consistency of diffusion, and the resulting alterations in strength caused by ultrasonic vibrational heat. …”
Get full text

CPG-Based Control of an Octopod Biomimetic Machine Lobster for Mining Applications: Design and Implementation in Challenging Underground Environments by Jianwei Zhao, Haokun Zhang, Mingsong Bao, Boxiang Yin, Yiteng Zhang, Zhen Jiang

“…Central pattern generators (CPGs) have been extensively researched and validated as a well-established methodology for bionic control, particularly within the field of legged robotics. …”
Get full text

Deciphering the complex links between inflammatory bowel diseases and NAFLD through advanced statistical and machine learning analysis by Deepak Kumar, Brijesh Bakariya, Chaman Verma, Zoltán Illés

“…There is an urgent need for non-invasive methods to diagnose various stages of liver dysfunction and uncover hidden pattern based on individual disease characteristics. …”
Get full text

Application of Machine Learning Techniques for Predicting Heating Coil Performance in Building Heating Ventilation and Air Conditioning Systems by Adam Nassif, Pasidu Dharmasena, Nabil Nassif

Get full text

Comparison of Induction Machine Drive Control Schemes on the Distribution of Power Losses in a Three-Level NPC Converter by Carlos A. Reusser, Matías Parra, Gerardo Mino-Aguilar, Victor R. Gonzalez-Diaz

“…Multilevel converters, in particular the three-level neutral point clamped (3L-NPC) topology driving medium-voltage induction machines, has become the most commonly adopted solution. …”
Get full text

Combination of gray level features with deep transfer learning for copra classification using machine learning and neural networks by A. Stephen Sagayaraj, T. Kalavathi Devi

“…These concatenated features were evaluated using various machine learning classifiers and neural networks. …”
Get full text

Annual global dengue dynamics are related to multi-source factors revealed by a machine learning prediction analysis. by Haoyu Long, Yilin Chen, Jingru Feng, Jian Chen, Xue Zhang, Wenjie Han, Min Kang, Xiangjun Du

“…Feature contribution pattern was different between hyperendemic and non-hyperendemic regions. …”
Get full text

Advanced machine learning technique for solving elliptic partial differential equations using Legendre spectral neural networks by Ishtiaq Ali

“…In this work, a novel approach based on a single-layer machine learning Legendre spectral neural network (LSNN) method is used to solve an elliptic partial differential equation. …”
Get full text

Unveiling the Spatial Heterogeneity of Urban Vitality Using Machine Learning Methods: A Case Study of Tianjin, China by Fengshuo Sun, Enxu Wang

“…Residential zones demonstrated higher nighttime UV than daytime UV on weekdays, with the opposite pattern observed on weekends. Public service zones maintained a comparable level of UV between the daytime and nighttime on weekdays. …”
Get full text

FORECASTING THE NUMBER OF AIRPLANE PASSENGERS USING HOLT WINTER'S EXPONENTIAL SMOOTHING METHOD AND EXTREME LEARNING MACHINE METHOD by Rochdi Wasono, Yulia Fitri, M. Al Haris

“…The Holt Winters Exponential Smoothing method is used because it aligns with the data pattern that includes trends and seasonality in the research, and it has a low level of accuracy. …”
Get full text

The machine psychology of cooperation: can GPT models operationalize prompts for altruism, cooperation, competitiveness, and selfishness in economic games? by Steve Phelps, Yvan I Russell

Get full text

Influence of Ocean Current Features on the Performance of Machine Learning and Dynamic Tracking Methods in Predicting Marine Drifter Trajectories by Huan Lin, Weiye Yu, Zhan Lian

“…In general, LSTM provides a more accurate geometric pattern of trajectories at the initial stages of forecasting, while DT offers superior accuracy in predicting specific trajectory positions. …”
Get full text

Source Analysis of Ozone Pollution in Liaoyuan City’s Atmosphere Based on Machine Learning Models and HYSPLIT Clustering Method by Xinyu Zou, Xinlong Li, Dali Wang, Ju Wang

“…Firstly, this study investigates the spatiotemporal distribution characteristics of the ozone (O₃) pollution in Liaoyuan City using monitoring data from 2015 to 2024. Then, three machine learning models (ML)—random forest (RF), support vector machine (SVM), and artificial neural network (ANN)—are employed to quantify the influence of meteorological and non-meteorological factors on O₃ concentrations. …”
Get full text

Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis by Lei Li, Hui Jing, Yuqi Zhao, Shenghua Wu, Boyu Zhu

Get full text

Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision by Chenglong Fan, Guanglin Yang, Cheng Li, Jiwen Cheng, Shaohua Chen, Hua Mi

“…The hub genes associated with DN and glycolysis-related clusters were identified via weighted gene co-expression network analysis (WGCNA) and machine learning algorithms. Finally, the expression patterns of these hub genes were validated using single-cell sequencing data and quantitative real-time polymerase chain reaction (qRT-PCR). …”
Get full text

Synergizing human insight and machine learning: A dual-lens approach to uncovering healthcare research and innovation outcomes by Stijn Horck, Sanne Steens, Jermain Kaminski

Get full text

The role of senescence-related genes in major depressive disorder: insights from machine learning and single cell analysis by Kun Lian, Wei Yang, Jing Ye, Yilan Chen, Lei Zhang, Xiufeng Xu

“…Using Random Forest (RF) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), we identified five hub SRGs to construct a logistic regression model. …”
Get full text