Enhancing Flow Direction in Geothermal Fields Using Sentinel-1 Data for Sustainability Water Management by Utama Widya, Anjasmara Ira Mutiara, Handayani Hepi Hapsari, Indriani Rista Fitri

“…The processed DEM data is used to extract key topographic parameters: elevation, slope, and curvature, which are then utilized in the model. …”
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A Hybrid Compact Convolutional Transformer with Bilateral Filtering for Coffee Berry Disease Classification by Biniyam Mulugeta Abuhayi, Andras Hajdu

“…Additionally, CCT-extracted features performed well with traditional classifiers, including Support Vector Machine (SVM) (82.47% accuracy; AUC 0.91) and Decision Tree (82.76% accuracy; AUC 0.86). …”
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Recent Advances in In Situ 3D Surface Topographical Monitoring for Additive Manufacturing Processes by Vignesh Suresh, Badrinath Balasubramaniam, Li-Hsin Yeh, Beiwen Li

“…Furthermore, the article discusses the state-of-the-art advancements in closed-loop feedback control systems, sensor fusion, and machine learning algorithms to integrate 3D surface data with various process signatures to dynamically adjust laser parameters and scan strategies. …”
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A Transfer Learning-Based VGG-16 Model for COD Detection in UV–Vis Spectroscopy by Jingwei Li, Iqbal Muhammad Tauqeer, Zhiyu Shao, Haidong Yu

“…To address these challenges, we introduce a transfer learning model based on VGG-16 for spectrum images. In this approach, parameters in the initial layers of the model are frozen, while those in the later layers are fine-tuned with the spectrum images. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…A mathematical framework comprising OCR system parameters (hardware, software, environment, and operational constraints) was developed to optimize uptime, accuracy, and cost-effectiveness. …”
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Design of an efficient dynamic context‐based privacy policy deployment model via dual bioinspired Q learning optimisations by Namrata Jiten Patel, Ashish Jadhav

“…Leveraging datasets including Adult (Census Income), Yelp, UC Irvine Machine Learning, and Movie Lens, the authors evaluate the model's performance against state‐of‐the‐art techniques, such as GEF AL, Deep Forest, and Robust Continual Learning. …”
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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops by Xin Yang, Xiaoying Yang, Jinhao Du

“…Reinforcement learning is employed to dynamically adjust temperature parameters, improving both exploration and exploitation capabilities and thus enhancing the convergence of the algorithm. …”
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Safety Risk Assessment of Double-Line Tunnel Crossings Beneath Existing Tunnels in Complex Strata by Bafeng Ren, Shengbin Hu, Min Hu, Zhi Chen, Hang Lin

“…This study demonstrates that optimized shield machine selection, improved lining design, interlayer soil reinforcement, the dynamic adjustment of shield parameters, and the precise measurement of shield posture significantly enhance the efficiency of shield tunneling and construction safety. …”
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DYNAMOMETRIC EQUIPMENT FOR MEASURING THE COMPONENTS OF CUTTING STRENGTHS WHEN PROCESSING MATERIALS WITH AXIAL TOOLS by R. V. Guseynov

“…The equipment is suitable for use in research laboratories of machine-building enterprises, universities and other scientific institutions.…”
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A New Framework for Dynamic Educational Marketing Segmentation in Student Recruitment: Optimizing Fuzzy C-Means with Metaheuristic Techniques by Rizal Bakri, Bobur Sobirov, Niken Probondani Astuti, Ansari Saleh Ahmar, Pawan Kumar Singh

“…This study also opens new directions for educational data mining research and machine-learning-based marketing strategies.…”
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Custom Network Quantization Method for Lightweight CNN Acceleration on FPGAs by Lingjie Yi, Xianzhong Xie, Yi Wan, Bo Jiang, Junfan Chen

“…Firstly, an improved PArameterized Clipping Activation (PACT) method is employed during the quantization aware training to restrict the value range of neural network parameters and reduce the loss of precision arising from quantization. …”
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A Comparative Analysis of Price Forecasting Methods for Maximizing Battery Storage Profits by Alessandro Fiori Maccioni, Simone Sbaraglia, Rahim Mahmoudvand, Stefano Zedda

“…We examined whether specific forecasting models, ranging from statistical benchmarks to machine learning methods, consistently deliver superior financial outcomes for storage operators. …”
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Empowering Retail in the Metaverse by Leveraging Consumer Behavior Analysis for Personalized Shopping: A Pilot Study in the Saudi Market by Monerah Alawadh, Ahmed Barnawi

“…Understanding consumer behavior and leveraging machine learning predictions based on analysis can significantly enhance user experiences, enabling personalized interactions and fostering overall engagement within the virtual environment. …”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…In this work, driven by the motivation of making DRL explainable, we developed a novel Explainable DRL (XDRL) approach for PM, integrating the Proximal Policy Optimization (PPO) DRL algorithm with the model agnostic explainable machine learning techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. …”
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Analysis of Exergy Efficiency and Ways of Energy Saving in Air Conditioning System for a Cleanroom by Dmytro Harasym, Volodymyr Labay

“…At the same time, cost parameters don’t allow making long term predicting. …”
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Be aware of overfitting by hyperparameter optimization! by Igor V. Tetko, Ruud van Deursen, Guillaume Godin

“…Abstract Hyperparameter optimization is very frequently employed in machine learning. However, an optimization of a large space of parameters could result in overfitting of models. …”
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Effects of Nb–Ti double microalloying on the grain structure and precipitates of hot compressed FeCrAl alloys by Xing Fan, Fei Wang, Hongming Wang, Bowen Zhao, Runze Li, Jun Zhou

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Investigation of Spectral Variations in Different Solar Photovoltaic Modules Using Spaceborne and In-Situ Hyperspectral Data by Shoki Shimada, Hiroki Mizuochi, Wataru Takeuchi

“…The combination of satellite imagery, especially multispectral imagery, with machine learning models has proven to be an effective tool for locating PVs. …”
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Uncertainty Analysis and Quantification of Rainfall-Induced Slope Instability in Fine-Grained Clayey Soils by Samuel A. Espinosa Fuentes, M. Hesham El Naggar

“…A dataset of 9984 slope scenarios was generated, supporting future machine learning applications for risk assessment and climate-resilient slope design.…”
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Site-specific prediction of O-GlcNAc modification in proteins using evolutionary scale model. by Ayesha Khalid, Afshan Kaleem, Wajahat Qazi, Roheena Abdullah, Mehwish Iqtedar, Shagufta Naz

“…Computational approaches, including protein language models and machine learning algorithms, have emerged as valuable tools for predicting O-GlcNAc sites, reducing experimental costs, and enhancing efficiency. …”
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