Forestry climate adaptation with HarvesterSeasons service—a gradient boosting model to forecast soil water index SWI from a comprehensive set of predictors in Destination Earth by Mikko Strahlendorff, Anni Kröger, Golda Prakasam, Miriam Kosmale, Mikko Moisander, Heikki Ovaskainen, Asko Poikela

“…The Copernicus Global Land Monitoring Service’s Soil Water Index (SWI) satellite-based observations from 2015 to 2023 at 10,000 locations in Europe were used as the predictand (target parameter) to train an artificial intelligence (AI) model to predict soil wetness with XGBoost (eXtreme Gradient Boosting) and LightGBM (Light Gradient Boosting Machine) implementations of gradient boosting algorithms. …”
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Multi-objective optimization design for accelerated degradation test based on game theory by Jinyan Guo, Zhiwu Han, Shuangfeng Wu, Junqi Long, Chuanhai Chen, Zhifeng Liu

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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study. by Giuliano Lorenzoni, Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…Recent research has evidenced that machine learning (ML) and natural language processing (NLP) tools and techniques have significantly benefited the diagnosis of depression. …”
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MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism by Yuanqi Chen, Aiping Wang, Ziyang Liu, Jie Yue, Enxu Zhang, Fei Li, Ning Zhang

“…This study introduces MoSViT, an innovative classification model leveraging advanced machine learning and computer vision technologies. …”
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Strengthening Low-Voltage Ride Through Competency of Doubly Fed Induction Generator Driven by Wind Turbine Using Super-Twisting Sliding Mode Control by Ashraf K. Abdelaal, Mohamed A. El-Hameed

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Advanced Deep Learning Methods to Generate and Discriminate Fake Images of Egyptian Monuments by Daniyah Alaswad, Mohamed A. Zohdy

“…We also studied truncation methods to regulate the generated image noise and identify the most effective parameter settings based on architectural representation versus diverse output creation. …”
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Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles by Naif Almakayeel

“…To efficiently counter new malware variants, novel techniques distinct from conventional methods must be utilized. Machine learning (ML) techniques cannot detect every new and complex malware variant. …”
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Rolling Bearing Fault Diagnosis Based on Optimized VMD and SSAE by Baoxian Chang, Xing Zhao, Dawei Guo, Siyu Zhao, Jiyou Fei

“…The feature set is then inputted into the deep machine learning model SSAE for training and testing. …”
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A Theoretical-Based Experimental Approach for Investigating the Charging of Insulators by Tareq H. Abbood, Hassan N. Al-Obaidi, Ali Mahdi, Wasan Kadhem, Faten Mousa, Huda Hussein

“…Keeping in mind that this parameter is by default recorded by the SEM machine itself. …”
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A First-Order Autoregressive Process with Size-Biased Lindley Marginals: Applications and Forecasting by Hassan S. Bakouch, M. M. Gabr, Sadiah M. A. Aljeddani, Hadeer M. El-Taweel

“…In addition, the unknown parameters of the model are estimated via the conditional least squares and Gaussian estimation methods. …”
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Multiscale Feature Modeling and Interpretability Analysis of the SHAP Method for Predicting the Lifespan of Landslide Dams by Zhengze Huang, Yuqi Bai, Hengyu Liu, Yun Lin

“…The model integrates CNN’s local feature extraction with Transformer’s global modeling capabilities, effectively capturing the nonlinear dynamics of key parameters affecting landslide dam lifespan. The IBKA ensures optimal parameter tuning, which enhances the model’s adaptability and generalization, especially when dealing with small-sample datasets. …”
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FW-S3KIFCM: Feature Weighted Safe-Semi-Supervised Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method by Shirin Khezri, Nasser Aghazadeh, Mahdi Hashemzadeh, Amin Golzari Oskouei

“…Semi-supervised clustering (SSC) methods have emerged as a notable research area in machine learning. These methods integrate prior knowledge of class distribution into their clustering process. …”
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Predicting discharge coefficient of triangular side orifice using ANN and GEP models by Mohamed Kamel Elshaarawy, Abdelrahman Kamal Hamed

“…This study utilized machine learning models to predict the discharge coefficient for a sharp-crested triangular side orifice (TSO). …”
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Sonic Affinity and Aesthetic Metamorphosis: The Nineteenth Century as a Turning Point in the History of Musical Thought by Javier Campos Calvo-Sotelo

“…The orchestra grew unstoppable, the piano doubled in power and possibilities compared to its predecessors, metronome and pianola became universal, and cultured compositions developed previously unthinkable features and complexity. Every formal parameter of music was affected: accents, tempo, melody, harmony, timbre, and intensity. …”
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INVESTIGATION ON WEAR-RESISTANT COATINGS FROM DIFFUSION-ALLOYED AUSTENITIC STEEL OBTAINED BY PLASMA SPRAYING AND SUBSEQUENT LASER PROCESSING by O. G. Devoino, A. F. Panteleenko

“…It is common knowledge that majority of machine parts and equipment has been out of service due to wear of surface layer. …”
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Informed circular fields: a global reactive obstacle avoidance framework for robotic manipulators by Marvin Becker, Philipp Caspers, Torsten Lilge, Sami Haddadin, Matthias A. Müller

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Advanced Cut-Edge Characterization Methods for Improved Sheared-Edge Damage Evaluation in High-Strength Sheet Steels by Patrick Larour, Olle Sandin, Daniel Casellas

“…It concludes that grain shear angle offers higher resolution. This parameter is therefore postulated as relevant for assessing the sheared-edge zone. …”
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Rolling Bearing Fault Diagnosis Method Based on Improved Variational Mode Decomposition and Information Entropy by Wen FAN, Lian GE, Xiaoting XIAO, Fangji GAN, Xin LAI, Hongxia DENG, Qi HUANG

“…However, VMD has the problem of parameter selection, which directly affects the performance of VMD processing, and causes mode aliasing. …”
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Enhancing Supply Chain Efficiency Resilience Using Predictive Analytics and Computational Intelligence Techniques by Lixing Bo, Jie Xu

“…PSO is applied to optimize inventory parameters, addressing multi-objective optimization problems in the supply chain. …”
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Exploring Process Heterogeneity in Environmental Statistics: Examples and Methodological Advances by Gregor Laaha, Johannes Laimighofer, Nur Banu Özcelik, Svenja Fischer

“…A tree-based machine learning model shows that prediction performance and model parameters vary with quantile loss optimization, suggesting the need for different or combined models for full time series in the presence of process heterogeneity. …”
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