Emotion Recognition Method Using U-Net Neural Network With Multichannel EEG Features and Differential Entropy Characteristics by Haitao Huang, Ying Deng, Bowen Hao, Wenguang Liu, Xiaoyu Tu, Guojun Zeng

“…This research not only provides a new approach to EEG emotion recognition but also holds substantial potential for applications in detecting psychological disorders and physical conditions in individuals from specialized occupational groups.…”
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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…The chosen model was integrated with a low-volume sprayer (50‒150 L·ha‒1), equipped with an electronic control unit for targeted spraying based on sensor-detected regions. The decision tree model achieved 89.9% testing accuracy, while the SVM model achieved 96.7% accuracy using hyperparameters: cost of 10.0 and tolerance of 0.001. …”
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An explainable RoBERTa approach to analyzing panic and anxiety sentiment in oral health education YouTube comments by Pradeep Kumar Yadalam, Mohamed Thaha, Prabhu Manickam Natarajan, Carlos M. Ardila

“…Although the model shows promise in detecting anxiety-inducing content, further optimization is needed.…”
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Explainable Aspect-Based Sentiment Analysis Using Transformer Models by Isidoros Perikos, Athanasios Diamantopoulos

“…Recently, transformers and large language models have demonstrated exceptional performance in detecting aspects and determining their associated sentiments within text. …”
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Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks by Haikun Shang, Yanlei Wei, Shen Zhang

“…Dissolved Gas Analysis (DGA) of transformer oil is a critical technique for transformer fault diagnosis that involves analyzing the concentration of gases to detect potential transformer faults in a timely manner. …”
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An explainable AI-based blood cell classification using optimized convolutional neural network by Oahidul Islam, Md Assaduzzaman, Md Zahid Hasan

“…This study presents an enhanced convolutional neural network (CNN) for detecting blood cells with the help of various image pre-processing techniques. …”
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Transfer learning for predicting of gross domestic product growth based on remittance inflows using RNN-LSTM hybrid model: a case study of The Gambia by Haruna Jallow, Ronald Waweru Mwangi, Alieu Gibba, Herbert Imboga

“…Pearson’s correlation was applied to detect and choose the variables that exhibit the strongest relationship with GDP and remittances. …”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…We train more than 900 different combination of feature selector, models and hyperparameters. At last, we assess the performance of the models on multiple performance measures (accuracy, sensitivity, specificity and area under the ROC curve (AUC)). …”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. …”
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Real-Time Road Crack Mapping Using an Optimized Convolutional Neural Network by M-Mahdi Naddaf-Sh, SeyedSaeid Hosseini, Jing Zhang, Nicholas A. Brake, Hassan Zargarzadeh

“…Then, the database was used to train a CNN whose hyperparameters were optimized using BOA. Finally, a heuristic algorithm is introduced to process the CNN’s output and produce the crack map. …”
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Sort & Slice: a simple and superior alternative to hash-based folding for extended-connectivity fingerprints by Markus Dablander, Thierry Hanser, Renaud Lambiotte, Garrett M. Morris

“…In contrast, sets of detected ECFP substructures are by default transformed into bit vectors using only a simple hash-based folding procedure. …”
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Machine Learning-Enhanced Discrimination of Gamma-Ray and Hadron Events Using Temporal Features: An ASTRI Mini-Array Analysis by Valentina La Parola, Giancarlo Cusumano, Saverio Lombardi, Antonio Alessio Compagnino, Antonino La Barbera, Antonio Tutone, Antonio Pagliaro

“…For every gamma-ray photon detected from even the brightest sources, thousands of cosmic-ray-induced atmospheric showers trigger the telescopes. …”
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Impact of Mother Wavelet Choice on Fast Wavelet Transform Performances for Integrated ST Segment Monitoring by Béatrice Guénégo, Caroline Lelandais-Perrault, Emilie Avignon-Meseldzija, Gérard Sou, Philippe Bénabès

“…We optimized their hyperparameters to minimize implementation complexity while satisfying the low-distortion constraints. …”
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