Spectral enhancement of PlanetScope using Sentinel-2 images to estimate soybean yield and seed composition by Supria Sarkar, Vasit Sagan, Sourav Bhadra, Felix B. Fritschi

“…Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images.…”
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Artificial Intelligence and Li Ion Batteries: Basics and Breakthroughs in Electrolyte Materials Discovery by Haneen Alzamer, Russlan Jaafreh, Jung-Gu Kim, Kotiba Hamad

“…In this study, we outlined the fundamental processes involved in applying AI to this domain, including data processing, feature engineering, model training, testing, and validation. …”
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Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating by N. Radhika, M. Sabarinathan, S. Sivaraman

“…Experimental validation confirms the model’s reliability, through minimal error deviation between predicted and actual values for porosity and hardness. …”
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Comparative Studies of Three-Dimensional Complex Flow Field Designs in a Proton Exchange Membrane Hydrogen Fuel Cell by Dilyan Gavrailov, Silviya Boycheva

“…The performance and durability of proton-exchange membrane fuel cells (PEMFCs) are dependent on fuel flow, humidifying water, and outgoing water management. …”
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Generative adversarial networks (GANS) for generating face images by Dolly Indra, Muh Wahyu Hidayat, Fitriyani Umar

“…Results indicate that training from scratch with the public dataset (FFHQ) using a batch size of 16 and a learning rate of 0.0025 achieves an FID score of 85.67 and performance of 86.46% at Tick 100, whereas the private dataset, under the same conditions, results in an FID score of 98.59 with a performance of 18.54%.. …”
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Detecting cognitive impairment in cerebrovascular disease using gait, dual tasks, and machine learning by Vânia Guimarães, Inês Sousa, Miguel Velhote Correia

“…Nested cross-validation was used for model training, hyperparameter tuning, and evaluation. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…Different cost functions have been tested and evaluated to improve the diagnostic performance. The proposed adaptive approach is model-free and eliminates the need for subsystem models, iterative algorithms, and extensive calibration procedures. …”
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Cyberbullying Detection, Prevention, and Analysis on Social Media via Trustable LSTM-Autoencoder Networks over Synthetic Data: The TLA-NET Approach by Alfredo Cuzzocrea, Mst Shapna Akter, Hossain Shahriar, Pablo García Bringas

“…In addition to this, we employ evaluation metrics that include the F1-score, accuracy, precision, and recall, to assess the performance of the models. Our model demonstrates outstanding performance across all the datasets by achieving a remarkable 99% accuracy and positioning itself as a frontrunner when compared to previous works that make use of the dataset featured in this research.…”
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Variance Reduction Optimization Algorithm Based on Random Sampling by GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang

“…Furthermore, a dynamic sample size adjustment strategy based on the performance evaluation model of computing unit is designed to improve the training efficiency. …”
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PERE: Prior-Enhanced and Resolution-Extended Object Detection for Industrial Laminated Panel Scenes by Haoyu Wang, Yiqiang Wu, Jinshuo Liang, Xie Xie

“…With prior knowledge, object detectors focus on updating model structures to improve performance. Despite initial success, most methods become increasingly complex and time-consuming for industrial applications while also neglecting the object distributions in the industrial dataset, especially in the context of industrial laminated panels. …”
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CNN–Transformer gated fusion network for medical image super-resolution by Juanjuan Qin, Jian Xiong, Zhantu Liang

“…The local branch uses the characteristic of dynamic convolution to adaptively adjust the convolution kernel parameters, which can enhance the feature extraction ability of convolutional neural network for multi-scale information and improve the detail restoration ability of the image without significantly increasing the network model size. …”
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Churn prediction for SaaS company with machine learning by Hugo Eduardo Sanches, Ayslan Trevizan Possebom, Linnyer Beatrys Ruiz Aylon

“…The study also explores feature performance, providing insights into attributes that influence customer churn, thereby guiding effective strategies. …”
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Detection of DRFM Deception Jamming Based on Diagonal Integral Bispectrum by Dianxing Sun, Ao Li, Hao Ding, Jifeng Wei

“…The transponder-style deception jamming implemented by Digital Radio Frequency Memory (DRFM) exhibits high similarity to real target radar echoes, while traditional detection methods suffer severe performance degradation under low signal-to-noise ratio (SNR) conditions. …”
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Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…EBM, LightGBM, and AdaBoost algorithms were applied to generate a discriminatory model between RA and controls. Comprehensive performance metrics were calculated, and the interpretability of the optimal model was assessed using global and local feature descriptions. …”
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A novel method to predict white blood cells after kidney transplantation based on machine learning by Songping He, Xiangxi Li, Zunyuan Zhao, Bin Li, Xin Tan, Hui Guo, Yanyan Chen, Xia Lu

“…Results As the final prediction model, the accuracy, sensitivity, specificity and area under the curve values of the multilayer perceptron model in test set were 71.34%, 61.18%, 82.28% and 77.30%, respectively. …”
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Distinguishing Human Journalists from Artificial Storytellers Through Stylistic Fingerprints by Van Hieu Tran, Yakub Sebastian, Asif Karim, Sami Azam

“…<b>Conclusions</b>: This research introduces an innovative approach to prompt engineering using the BERTopic modelling technique and identifies key stylistic features to distinguish AI-generated content from human-generated content. …”
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Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, E... by Daniel Niguse Mamo, Tesfahun Melese Yilma, Makda Fekadie Tewelgne, Yakub Sebastian, Tilahun Bizuayehu, Mequannent Sharew Melaku, Agmasie Damtew Walle

“…Then, seven supervised classification machine-learning algorithms for model development were trained. The performances of the predictive models were evaluated using accuracy, sensitivity, specificity, precision, f1-score, and AUC. …”
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Micro-variations in timing and loudness affect music-evoked mental imagery by Ceren Ayyildiz, Andrew J. Milne, Muireann Irish, Steffen A. Herff

“…Yet, the role of specific musical features in these effects remains elusive. One important aspect of human musical performances is the presence of micro-variations—small deviations in timbre, pitch, and timing, driven by motor and attentional processes. …”
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Ethical Responsibility of Neuromarketing Companies in Harnessing the Market Research – a Global Exploratory Approach by Nicolae Al. Pop, Dan-Cristian Dabija, Ana Maria Iorga

“…It starts with analysing a traditional persuasion model that has inherently been influenced by the neuromarketing research features. …”
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Object Recognition and Positioning with Neural Networks: Single Ultrasonic Sensor Scanning Approach by Ahmet Karagoz, Gokhan Dindis

“…A deep learning model demonstrated by this work extracts object features using convolutional neural networks (CNNs) and performs coordinate estimation using regression layers. …”
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