Interpretable machine learning for atomic scale magnetic anisotropy in quantum materials by Jan Navrátil, Rafał Topolnicki, Michal Otyepka, Piotr Błoński

“…To address this, we developed a machine learning (ML) model trained on scalar-relativistic DFT data using a tree-based gradient boosting approach. …”
Get full text

Predicting concrete strength using machine learning and fresh-state measurements by Bahdan Zviazhynski, Callum White, Janet M. Lees, Gareth J. Conduit

“…This study concludes that optimizing solely for accuracy selects a different model than optimizing with the proposed unified accuracy and uncertainty metric. …”
Get full text

Machine learning in additive manufacturing——NiTi alloy’s transformation behavior by Lidong Gu, Kongyuan Yang, Hongchang Ding, Zezhou Xu, Chunling Mao, Panpan Li, Zhenglei Yu, Yunting Guo, Luquan Ren

“…Using this model, the study identified a novel, larger window of optimal LPBF processing that allows for controllable complex phase transitions.…”
Get full text

Machine Learning Analysis of Maize Seedling Traits Under Drought Stress by Lei Zhang, Fulai Zhang, Wentao Du, Mengting Hu, Ying Hao, Shuqi Ding, Huijuan Tian, Dan Zhang

“…The findings indicated that plant height, aboveground weight, and chlorophyll content constituted the primary indices for phenotyping maize seedlings under drought conditions. The XGBoost model demonstrated optimal performance in the classification (AUC = 0.993) and regression (R² = 0.863) tasks, establishing itself as the most effective prediction model. …”
Get full text

Predicting mortgage credit defaults in morocco using machine learning approaches by Amine Hade, Mohamed Elhia

“…Although its precision is slightly lower than that of the other two models, BaggingClassifier compensates for this with a superior F1-score, reflecting an optimal balance between precision and recall. …”
Get full text

Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…This paper considers the single-machine scheduling problem of total tardiness minimization. …”
Get full text

Design and Testing of an Offset Straw-Returning Machine for Green Manures in Orchards by Quanzhong Zhang, Jinfei Zhao, Xiaowen Yang, Ling Wang, Guangdong Su, Xinying Liu, Chuang Shan, Orkin Rahim, Binghui Yang, Jiean Liao

“…The development of this machine and the construction of its parameter model can provide a certain reference value for developing and optimizing related machines including green manure-returning machines.…”
Get full text

SIMULATION OF LINEAR POSITION HYDRAULIC DRIVE FOR MACHINE POWER DRILL FEED by Valentin Sergeyevich Sidorenko, Le Trung Kien

Get full text

Global trends in machine learning applications for single-cell transcriptomics research by Xinyu Liu, Zhen Zhang, Chao Tan, Yinquan Ai, Hao Liu, Yuan Li, Jin Yang, Yongyan Song

“…Future directions should optimize deep learning architectures, enhance model generalization capabilities, and promote technical translation through multi-omics and clinical data integration. …”
Get full text

Integration of the reptile search algorithm and the adaptive neuro-fuzzy inference system enhances standardized precipitation evapotranspiration index forecasting by Zahra Kayhomayoon, Mohammad Javad Bahmani, Sami Ghordoyee Milan, Ommolbanin Bazrafshan, Ronny Berndtsson

Get full text

Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts by Marcin Gołaszewski, Marcin Królikowski, Bartosz Powałka

Get full text

Parallel Machine Production and Transportation Operations’ Scheduling with Tight Time Windows by Yang Jiang, Tong He, Jie Xiong, Xin Wu, Yao Chen

“…The orders located at the parallel machines need to be delivered to customers by train. …”
Get full text

A Comprehensive Review of Machine Learning Approaches for Flood Depth Estimation by Bo Liu, Yingbing Li, Minyuan Ma, Bojun Mao

“…The findings indicate that machine learning models excel in handling large-scale complex data and nonlinear relationships, and their performance can be further optimized through combinations with various models, significantly enhancing the accuracy and efficiency of flood depth estimation. …”
Get full text

Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…The research incorporates a hybrid GA-Neural Network (NN) model further, using machine learning to speed up fitness evaluation and provide optimal settings for OCR performance improvement that is applicable in real world. …”
Get full text

Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification by Sylvio Barbon, Ana Paula Ayub da Costa Barbon, Rafael Gomes Mantovani, Douglas Fernandes Barbin

“…The proposed methodology was conducted with a support vector machine algorithm (SVM) to compare the precision of the proposed model. …”
Get full text

An IMU-Based Machine Learning System for Container Collision Position Identification by Xin Zhang, Zihan Song, Do-Myung Park, Byung-Kwon Park

“…This study leverages data from an Inertial Measurement Unit sensor and evaluates combinations of machine learning models and feature selection methods to identify the optimal approach for collision position detection. …”
Get full text

Exploring explanation deficits in subclinical mastitis detection with explainable boosting machines by Changhong Jin, John Upton, Brian Mac Namee

“…The study compares models built with readily available data from milking machines to those using more expensive milk characteristic data to determine if there’s an “explanation deficit” when relying on the cheaper, more accessible data. …”
Get full text

Improving Osteosarcoma Detection through SMOTE-Driven Machine Learning Approaches by Muhammad Ainul Fikri, Ajie Kusuma Wardhana, Yudha Riwanto, Inggrid Yanuar Risca Partiwi, Fauzia Sekar Anis Sekar Ningrum, Iqbal Kurniawan Asmar Putra

“…This study proposes a lightweight AI approach that optimizes osteosarcoma detection while maintaining high diagnostic accuracy, leveraging machine learning models under 5MB, manually or semi-automatically extracted features, and SMOTE for data balancing. …”
Get full text

Machine learning for detection of equivariant finite symmetry groups in dynamical systems by Pablo Calvo-Barlés, Sergio G Rodrigo, Luis Martín-Moreno

Get full text

From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

“…Our approach systematically compares traditional machine learning classifiers (Naïve Bayes, SVMs, Random Forest) with state-of-the-art deep learning models, such as CNNs, LSTMs, and BERT, while incorporating optimized vectorization techniques, including TF-IDF, Word2Vec, and contextual embeddings. …”
Get full text