Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…Hyperparameter optimization techniques showed minimal improvement in model performance, suggesting that the transformations effectively captured the underlying relationships in the data. …”
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Expansion Planning of Electrical Distribution Systems Considering Voltage Quality and Reliability Criteria by Marco Israel Zuñiga Villarreal, Alexander Aguila Téllez, Narayanan Krishnan, Marcelo García

“…The proposed algorithm recommended upgrades to electrical conductors without significantly affecting the system costs. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…Results indicated that RF and SVR performance improved primarily with feature selection, while PLSR was most influenced by data smoothing. …”
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Comparative effect of traditional and collaborative watershed management approaches on flood components by Ali Nasiri Khiavi, Mehdi Vafakhah, Seyed Hamidreza Sadeghi, Changhyun Jun, Sayed M. Bateni

“…Abstract Identifying the critical areas of flood generation and determining the optimal measures for flood control and management (FCM) is one of the most important basics of watershed management. …”
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Enhancing grid-connected PV-EV charging station performance through a real-time dynamic power management using model predictive control by Aziz Watil, Hamid Chojaa

“…It also provides flexibility in BEV power sizing, optimizing the use of power electronics converters to reduce costs and complexity. …”
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FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images by Liang Zhou, Achin Jain, Arun Kumar Dubey, Sunil K. Singh, Neha Gupta, Arvind Panwar, Sudhakar Kumar, Turki A. Althaqafi, Varsha Arya, Wadee Alhalabi, Brij B. Gupta

“…Abstract Cancer is among the most dangerous diseases contributing to rising global mortality rates. …”
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RuleKit2: Faster and simpler rule learning by Adam Gudyś, Cezary Maszczyk, Joanna Badura, Adam Grzelak, Marek Sikora, Łukasz Wróbel

“…Here we present its second version. New algorithms and optimized implementations of those previously included, significantly improved the computational performance of our suite, reducing the analysis time of some data sets by two orders of magnitude. …”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…Discussion The e4Quant assay offers a rapid, cost-effective, and highly accurate biochemical alternative to APOE genotyping, suitable for clinical and research settings, particularly in assessing AD risk and optimizing anti-amyloid therapeutic strategies. …”
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SiCRNN: A Siamese Approach for Sleep Apnea Identification via Tracheal Microphone Signals by Davide Lillini, Carlo Aironi, Lucia Migliorelli, Leonardo Gabrielli, Stefano Squartini

“…The final detection of <i>apnea</i> events is performed using an unsupervised clustering algorithm, specifically <i>k-means</i>. Multiple experimental runs were carried out to determine the optimal network configuration and the most suitable type and frequency range for the input data. …”
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An ensemble time-embedded transformer model for traffic conflict prediction at RRFB pedestrian crossings by Md Jamil Ahsan, Mohamed Abdel-Aty, B M Tazbiul Hassan Anik, Zubayer Islam

“…Insights from the study can optimize RRFB performance by identifying conflict times and locations, improving driver alerts during peak hours, and ensuring smoother traffic flow and reliability.…”
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ABL-SMOTE: A Novel Resampling Method by Handling Noisy and Borderline Challenge for Imbalanced Dataset for Software Defect Prediction by Kamal Bashir, Sara Abdelwahab Ghorashi, Ali Ahmed, Abdolraheem Khader

“…Machine learning algorithms face important implementation difficulties due to imbalanced learning since the Synthetic Minority Oversampling Technique (SMOTE) helps improve performance through the creation of new minority class examples in feature space before preprocessing. …”
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Postmarketing safety evaluation of pemetrexed using FAERS and JADER databases by Luo Lv, Xiangyang Wu, Yubo Ren, Yuli Guo, Haixiong Wang, Xiaofang Li

“…Continuous pharmacovigilance is essential to optimize its clinical use and improve patient safety.…”
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The impact of Poyang Lake water level changes on the landscape pattern of wintering wading bird habitats by Feihong Yu, Jiancheng Zhai, Zhiqiang Huang, Jimei Chen, Fuqiang Han, Liaobo Wang

“…The cyclical rhythm of water level changes determines the dynamic variations in the wetland landscape pattern of Poyang Lake, directly impacting the habitat and survival of wintering migratory birds, particularly wading birds, which are most sensitive to these changes. This study employs an Artificial Neural Network (ANN) algorithm to interpret wetland landscapes using the Gao-Fen Satellite Images across 14 different water levels. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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Machine learning-based prediction of physical parameters in heterogeneous carbonate reservoirs using well log data by Fuyong Wang, Xianmu Hou

“…The results demonstrate that GPR achieves the highest accuracy in porosity prediction, with a coefficient of determination (R2) value of 0.7342, while RF proves to be the most accurate for permeability prediction. Despite these improvements, accurately predicting low-permeability zones in heterogeneous carbonate rocks remains a significant challenge. …”
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Empowering Sustainability: The Crucial Role of IoT-Enabled Distributed Learning Systems in Reducing Carbon Footprints by Anjana M S, Aryadevi Remanidevi Devidas, Maneesha Vinodini Ramesh

“…Transitioning to cleaner energy sources and improving energy efficiency are essential steps to reduce the environmental impact of electricity generation. …”
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Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…This study evaluates several leading multiobjective BO acquisition functions–namely, parallel expected hypervolume improvement (qEHVI), noisy qEHVI, parallel parEGO, and parallel noisy parEGO (qNparEGO)–in optimizing the physical properties of multi-component alloys. …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Medical images (9/26, 34.6%) and electronic medical records (7/26, 26.9%) were the most commonly used data types. Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. …”
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Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study by Emanuele Frassini, Teddy S. Vijfvinkel, Rick M. Butler, Maarten van der Elst, Benno H. W. Hendriks, John J. van den Dobbelsteen

“…We employed only the clinical phases derived from video analysis as input to the algorithms. Our results show that InceptionTime and LSTM-FCN yielded the most accurate predictions. …”
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2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration by Ke-Yu Yao, Derek Ka-Hei Lai, Hyo-Jung Lim, Bryan Pak-Hei So, Andy Chi-Ho Chan, Patrick Yiu-Man Yip, Duo Wai-Chi Wong, Bingyang Dai, Xin Zhao, Siu Hong Dexter Wong, James Chung-Wai Cheung

“…Herein, we present an environmentally friendly, low-cost, and nonionic fabrication approach for a 2H-phase molybdenum disulfide (2H-MoS2)-enhanced multi-walled carbon nanotube (MWCNT) strain sensor, developed via a systematically optimized vacuum-assisted filtration process. …”
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