Individual differences in probabilistic learning and updating predictive representations in individuals with obsessive-compulsive tendencies by Bianka Brezóczki, Bence Csaba Farkas, Flóra Hann, Orsolya Pesthy, Eszter Tóth-Fáber, Kinga Farkas, Katalin Csigó, Dezső Németh, Teodóra Vékony

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Optimizing Apache Spark MLlib: Predictive Performance of Large-Scale Models for Big Data Analytics by Leonidas Theodorakopoulos, Aristeidis Karras, George A. Krimpas

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Development of a methodology for optimizing the component composition of the charge for the processing of gts of steelmaking, providing the efficiency of useful components extracti... by S. L. Rimoshevskij, D. M. Golub, D. A. Prokopchuk

“…The article deals with the recycling issues of electric steelmaking dusts by thermodynamic extraction of iron, zinc and lead in order to reduce the impact on the environment and increase the industry resource base.The purpose of the research was to determine the influence of the quantitative content of low-calorie and high-calorie carbon on the processes of zinc oxide reduction in gas purification dust and its further sublimation using a vacuum in a closed system of a resistance heating furnace. …”
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A novel formula for predicting the ultimate compressive strength of the cylindrically curved plates by Do Kyun Kim, Andy Ming King Wong, Jinha Hwang, Shen Li, Nak-Kyun Cho

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A Multi‐Model Ensemble of Baseline and Process‐Based Models Improves the Predictive Skill of Near‐Term Lake Forecasts by Freya Olsson, Tadhg N. Moore, Cayelan C. Carey, Adrienne Breef‐Pilz, R. Quinn Thomas

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Predictive Modeling of Yoga's Impact on Venous Clinical Severity Scoring Using Gaussian Process Classification and Advanced Optimization Algorithms by Yazdan Ashgevari, Faranak Kazemi

“…The study employs the Adaptive Opposition Slime Mould Algorithm (AOSM) and Mountain Gazelle Optimizer (MGO) to enhance the predictive capabilities of a Gaussian Process Classification (GPC) model. …”
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Investigating the Predictive Performance of Process Data and Result Data in Complex Problem Solving Using the Conditional Gradient Boosting Algorithm by Fatma Nur Aydin, Kubra Atalay Kabasakal, Ismail Dilek

“…This study aims to examine the predictive performance of process data and result data in complex problem-solving skills using the conditional gradient boosting algorithm. …”
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Effect of treatment process on the formability of Fe–Al alloy powders and the crushing strength of green compacts by DENG Ying, WU Yin-jiang, NAN Hai-juan, LIANG Yong-ren, MENG Qiang

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Direct reduction of vanadium titanium pellets using ammonia as a reductant: Thermodynamics, characteristics, and kinetics analysis by Yuejun Liu, Xianchun Li, Shaoyan Wang, Li Li

“…The highest concentration of nitric oxide (NO) during the reduction process can reach 198 ppm, and NO will gradually decrease as the reaction progresses. …”
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Performance Evaluation of Real-Time Image-Based Heat Release Rate Prediction Model Using Deep Learning and Image Processing Methods by Joohyung Roh, Sehong Min, Minsuk Kong

Subjects: “…HRR prediction…”
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Effect of Reduction Ratio below Austenite Recrystallization Stop Temperature on Mechanical Properties of an API X70M PSL2 Line Pipe Steel by Ramazan Tütük, Eyüp Sabri Kayalı, Mustafa Merih Arıkan

“…It wasobserved that final grain size decreased and strength and toughness increasedwith increasing reduction ratio.…”
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Neural network technology for processing of signals from technical objects control means by A. A. Doudkin, Y. Y. Marushko

“…A distinctive feature of this is the possibility of additional training in the case of analyzing parameters in a non-stationary environment, providing operational processing of the entire set of telemetry parameters of the technical object, increasing the accuracy of identification and prediction of the state of the object by telemetric information with incomplete and noisy input data. …”
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Recent Trends and Advances in Utilizing Digital Image Processing for Crop Nitrogen Management by Bhashitha Konara, Manokararajah Krishnapillai, Lakshman Galagedara

“…A total of 95 articles remained after the screening and selection process. Interest in integrating machine learning and deep learning algorithms with DIP has increased, with the frequently used algorithms—Random Forest, Support Vector Machine, Extreme Gradient Boost, and Convolutional Neural Networks—achieving higher prediction accuracy levels. …”
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Application of Turbo-Expander for Greenhouse Gas and Air Pollutant Emissions Reduction Using Exergy and Economical Analysis by E. GhasemiKafrudi, M. Amini, M. R. Habibi

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Toward Green Liquid Nitrogen Fertilizer Synthesis: Plasma‐Driven Nitrogen Oxidation and Partial Electrocatalytic Reduction by Zhongping Qu, Jungmi Hong, Yuting Gao, Jing Sun, Jingwen Huang, Mingyan Zhang, Mengying Zhu, Tianyu Li, Xiangyu Wang, Dingwei Gan, Qiang Song, Tianqi Zhang, Rusen Zhou, Dingxin Liu, Patrick J. Cullen, Renwu Zhou

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Optimization of Graphene Oxide’s Characteristics with TOPSIS Using an Automated Decision-Making Process by Javanbakht T.

Subjects: “…process innovation…”
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Constrained reduced-order modeling using bounded Gaussian processes for physically consistent reacting flow predictions by Muhammad Azam Hafeez, Alberto Procacci, Axel Coussement, Alessandro Parente

“…These surrogate models are built in a data-driven manner by combining computational fluid dynamics simulations with Proper Orthogonal Decomposition (POD) for dimensionality reduction and Gaussian Process Regression (GPR) for nonlinear regression. …”
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Hot Metal Temperature Prediction During Desulfurization in the Ladle by Milan Durdán, Ján Terpák, Marek Laciak, Ján Kačur, Patrik Flegner, Gabriel Tréfa

Subjects: “…desulfurization process…”
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Optimization of green tea extract, rosemary extract, and rice bran in multifunctional bread: A concept for reduction of acrylamide and phytic acid by Mandana Tayefe, Leili Fadayi Eshkiki, Zahra Rahbar Dalir, Azin Nasrollahzadeh Masoule

“…This research aimed to produce a multifunctional bread by adding hydrothermally processed rice bran (RB), green tea extract (GTE), and rosemary extract (RE). …”
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A cutter contacting point trajectory prediction method combining harmonic functions and dimensionality reduction for improving machining precision in flat-end milling by Liangji Chen, Haohao Xu, Huiying Li, Hansong Gao, Haixiong Wang

“…A harmonic function is then utilized to predict CC point trajectories, enabling effective compensation for identified errors. …”
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