Predicting Corn Moisture Content in Continuous Drying Systems Using LSTM Neural Networks by Marko Simonič, Mirko Ficko, Simon Klančnik

“…By using innovative technologies such as machine learning, neural networks, and LSTM modeling, a predictive model was implemented for past data that include various drying parameters and weather conditions. …”
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Micromilling of Ti-6Al-4V alloy for high-aspect-ratio thin walls and dimensional error compensation based on an online compensation system by Y. Li, X. Cheng

“…Comparisons of the effects of tool shape on cutting force, cutting temperature, thin wall dimension error, tool wear, and surface morphology are analyzed systematically, and the optimal cutting edge shape has been identified. Second, a deformation prediction model for micromilling of titanium alloy is established and calibrated. …”
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Improving Manufacturing Supply Chain by Integrating SMED and Production Scheduling by Viren Parwani, Guiping Hu

“…Scheduling an operating procedure within SMED in such case is a challenge. Project scheduling model with workforce constraints can be used to create a set of heuristics to provide us with an optimized list of tasks. …”
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Test-Time Training with Adaptive Memory for Traffic Accident Severity Prediction by Duo Peng, Weiqi Yan

“…Traffic accident prediction is essential for improving road safety and optimizing intelligent transportation systems. However, deep learning models often struggle with distribution shifts and class imbalance, leading to degraded performance in real-world applications. …”
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ANN-SVM-IP: An Innovative Method for Rapidly and Efficiently Detecting and Classifying of External Defects of Apple Fruits by Nashaat M. Hussain Hassan, Mohamed M. Hassan Mahmoud, Mohamed A. Ismeil, M. Mourad Mabrook, A. A. Donkol, A. M. Mabrouk

“…The second phase is designed to accurately and effectively classify five Apple fruit defects (Healthy, Full-Damage, Bloch, Rot, and Scab) an optimized ML (Machine Learning) algorithm, which relied combining ANN (Artificial neural network) and SVM (Support Vector Machine) techniques. …”
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Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based on 18F-FDG PET/CT radiomics by Xuefeng Hou, Kun Chen, Huiwen Luo, Wengui Xu, Xiaofeng Li

“…Whereas, the KNN model was confirmed as the optimal model to distinguish HER2-zero-expression from others, with an AUC value of 0.929 (95%CI: 0.890–0.958), 0.847 (95%CI: 0.764–0.910), and 0.835 (95%CI: 0.762–0.908) in the training set, independent validation set, and external validation set. …”
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A benchmark for evaluating crisis information generation capabilities in LLMs by Ruilian Han, Lu An, Wei Zhou, Gang Li

“…A combination of manual and machine scoring methods was utilized. This approach ensured a comprehensive understanding of each model's performance. …”
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Pig Detection Algorithm Based on Sliding Windows and PCA Convolution by Longqing Sun, Yan Liu, Shuaihua Chen, Bing Luo, Yiyang Li, Chunhong Liu

“…A two-level support vector machine model was trained to calculate the probabilities of sliding windows by using gradient and gray distribution features of pigs. …”
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PerGOLD: Identification of offensive language in Persian tweets: leveraging crowdsourcing by Fatemeh Jafarinejad, Marziea Rahimi, Maryam Khodabakhsh, Seyedehfatemeh Karimi

“…Finally, we evaluated the efficiency of these data by applying some classic machine learning models (LR, SVM) and transformer-based language models (RoBERTa, ParsBERT). …”
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Crop Monitoring System Using IoT, Solar Energy and Decision Tree Algorithm by Ricardo Yauri, Luis Cuyubamba, Stefano Nuñez

“…Peru's diverse topographical regions offer optimal conditions for agriculture, but a lack of technology hinders efficiency, leading to food imports despite the country's potential. …”
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18F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study by Chunxiao Sui, Qian Su, Kun Chen, Rui Tan, Ziyang Wang, Zifan Liu, Wengui Xu, Xiaofeng Li

“…Furthermore, the combined model integrating the optimal radiomic model with the clinical model achieved an improved C-index of 0.747. …”
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Voltage Control Nonlinearity in QZSDMC Fed PMSM Drive System with Grid Filtering by Przemysław Siwek, Konrad Urbanski

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Impact of family doctor contracted services on the health of migrants: a cross-sectional study in China by Sijia Liu, Jiajing Hu

“…The study employs a double machine learning model to estimate the effect of family doctor contracted services (FDCS) on migrants’ self-rated health (MSRH). …”
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FL-TENB4: A Federated-Learning-Enhanced Tiny EfficientNetB4-Lite Approach for Deepfake Detection in CCTV Environments by Jimin Ha, Abir El Azzaoui, Jong Hyuk Park

“…The proposed architecture integrates Tiny Machine Learning (TinyML) techniques with EfficientNetB4-Lite, a lightweight convolutional neural network optimized for edge devices, and employs a Federated Learning (FL) approach for collaborative model updates. …”
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A Yarn Quality Prediction Method Based on M-ESTIMATOR Robust Broad Learning System With Tightly Cascaded Feature Layers by Baowei Zhang, Zhilin Guo, Yonghua Wang

“…Aiming at the problem that multilayer neural networks rely on large datasets and broad learning system (BLS) cannot cope well with outliers in data of yarn production, which leads to low accuracy and stability when used for predicting yarn quality, we propose a robust broad learning system with the ability to resist the interference of outliers and optimize its ability to extract features. First, the feature mapping groups of the BLS were connected in a tightly cascaded manner to improve the model’s ability to express the features of the parameters of raw cotton and machine operation. …”
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Neural Network Approach for Fatigue Crack Prediction in Asphalt Pavements Using Falling Weight Deflectometer Data by Bishal Karki, Sayla Prova, Mayzan Isied, Mena Souliman

“…This study’s findings provide valuable insights for pavement maintenance and rehabilitation planning, helping transportation agencies optimize repair schedules and reduce costs. This research highlights the growing role of AI in pavement engineering, demonstrating how machine learning can improve infrastructure management. …”
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Artificial Intelligence Driven Human Identification by Purushottam Sharma, Aazar Imran Khan, Samyak Jain, Abhishek Srivastava

“…A Receiver Operating Characteristic Curve (ROC) is obtained for comparison of the proposed model with other machine learning models to better understand the efficiency of the system…”
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NATE: Non-pArameTric approach for Explainable credit scoring on imbalanced class. by Seongil Han, Haemin Jung

“…In contrast, tree-based machine learning models often provide enhanced predictive performance but struggle with interpretability. …”
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The Formation of Artificial Data based on a Conveyor Enterprise by A. V. Zaripov, R. S. Kulshin, A. A. Sidorov

“…The test results showed a high accuracy of the trained model, with an mAP50 of 0.95, indicating the significant potential of synthetic data for improving the quality of machine learning models. …”
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Financial accounting management strategy based on business intelligence technology for sustainable development strategy by Jianben Feng

“…The experimental results show that the proposed model achieves an accuracy of 67.47% in predicting financial distress, a recall rate of 72.36%, an F1 value of 68.58%, and a misclassification rate of less than 4%, which are all superior to traditional methods such as K-nearest neighbor, support vector machine and convolutional neural network. …”
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