PERSPECTIVES OF MOLIBDENUM CONTAINING MATERIALS APPLICATION FOR ALLOYING OF IRONCARBON ALLOYS DURING MANUFACTURING OF CRITICAL CASTINGS by A. G. Slutsky, A. S. Kalinichenko, R. E. Trubitsky, V. A. Sheinert

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Research progress of Ti2AlNb alloy and feasibility analysis of its application in aero engines by PEI Huiping, LIU Dong, YAO Lipan, SHAO Tianmin, LIU Qiaomu, LIU Liangliang, CHEN Qianming

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Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

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REVIEW OF «WHY WE CANNOT PREDICT STRONG EARTHQUAKES IN THE EARTH’S CRUST» BY I.L. GUFELD, M.I. MATVEEVA AND O.N. NOVOSELOV by Alexey V. Nikolaev

Subjects: “…seismic process…”
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Optimization of Energy-saving Operation Strategy of Heat Pump Hot-water System Using Stochastic Load Prediction by Liu Chengning, Liang Xingyu, Shao Liangliang, Zhang Chunlu

“…To address this issue, a method of operation strategy optimization using stochastic load prediction was developed in this study. The method adopts multiple stochastic process samplings to simulate the uncertainty of the load prediction, thereby improving the robustness and energy savings of the operation strategy. …”
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Cross-modality transfer for DED-LB/M: AI-based prediction of schlieren phenomena from coaxial imaging by Benedikt Brandau, João Sousa, Rico Hemschik, Frank Brueckner, Alexander F.H. Kaplan

“…The results demonstrate that artificial intelligence-based analysis of coaxial imaging can provide schlieren-equivalent process information, making it possible to monitor refractive index variations, detect process deviations and improve defect prediction in real time. …”
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THE METHODS OF EXTRAPOLATING A VECTOR RANDOM PROCESS BASED ON THE CANONICAL DECOMPOSITION USING THE METHOD OF INTEGRAL ASSESSMENTS FOR A CERTAIN INTERVAL WHEN DETERMINING OF RANDOM... by Rustam K. Murasov

Subjects: “…prediction vector random process…”
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Unlocking Bioethanol Production Potential: A Computational Exploration of Agri-Food Waste Valorization in Circular Bioeconomy Using Metagenomic Mining and Process Prediction Tools by Radu Tamaian, Corina-Teodora Ciucure, Elisabeta-Irina Geană

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Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming by Mohammed Yunus, Mohammad S. Alsoufi

“…This paper both defines and illustrates how GP can be applied to the FSW process to derive precise relationships between the output and input parameters in order to obtain a generalized prediction model. …”
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Prediction of the Atomization Process in Respimat^® Soft Mist^TM Inhalers Using a Volume of Fluid-to-Discrete Phase Model by Ted Sperry, Yu Feng

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Ocean alkalinity enhancement approaches and the predictability of runaway precipitation processes: results of an experimental study to determine critical alkalinity ranges for safe and sustainable application scenarios by N. Suitner, G. Faucher, C. Lim, J. Schneider, C. A. Moras, U. Riebesell, J. Hartmann

“…Incorporating such stability and loss patterns into ocean biogeochemical models, which are capable of resolving dilution processes of treated and untreated water parcels, would, from a geochemical perspective, facilitate the prediction of safe local application levels of OAE. …”
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Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model. by Jonathan Halama, Robert McKane, Bradley Barnhart, Paul Pettus, Allen Brookes, Kevin Djang, Vivian Phan, Sonali Chokshi, James Graham

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Interpretable Machine Learning for High-Accuracy Reservoir Temperature Prediction in Geothermal Energy Systems by Mohammadali Ahmadi

“…This study conducts a comprehensive comparative analysis of advanced machine learning models, including support vector regression (SVR), random forest (RF), Gaussian process regression (GP), deep neural networks (DNN), and graph neural networks (GNN), to evaluate their predictive performance for reservoir temperature estimation. …”
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Hemispheric contribution to vertex augmentation/reduction of the auditory evoked potential by C. Collin, F. Lolas

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Multi-Task Prediction Method Based on GGCN for Object Centric Event Logs by Li Ke, Fang Huan, Xu Yifei, Shao Chifeng

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Compression-based Data Reduction Technique for IoT Sensor Networks by Suha Abdulhussein Abdulzahra, Ali Kadhum M. Al-Qurabat, Ali Kadhum Idrees

“…In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. …”
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Metabolic modeling of endosymbiont genome reduction on a temporal scale by Keren Yizhak, Tamir Tuller, Balázs Papp, Eytan Ruppin

“…By optimizing this correlation across the space of potential growth and biomass conditions, we compute an upper bound estimate on the model's prediction accuracy (R=0.54). The model's network‐based predictive ability outperforms predictions obtained using genomic features of individual genes, reflecting the effect of selection imposed by metabolic stoichiometric constraints. …”
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Alkaline Amino Acids for Salt Reduction in Surimi: A Review by Tong Shi, Guxia Wang, Yu Xie, Wengang Jin, Xin Wang, Mengzhe Li, Yuanxiu Liu, Li Yuan

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Predicting tilling and seeding operation times in grain production: A comparison of machine learning and mechanistic models by Luca Scheurer, Tobias Zimpel, Joerg Leukel

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A systematic review on the impact of breastfeeding on cancer risk, weight loss, cardiovascular disease, type 2 diabetes mellitus in mothers, and the role of fathers, medical person... by Olga Krupa, Daria Rybak, Katarzyna Kamińska-Omasta, Bartosz Omasta, Kuba Borys Romańczuk, Magdalena Agata Czerska, Paulina Dorota Pietrukaniec, Szymon Przemysław Stolarczyk, Zofia Martyna Wójcik, Kinga Furtak

Subjects: “…breastfeeding and cancer risk reduction…”
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