Numerical simulation of optimal inlet air temperature of a forced convective fish cabinet rotary dryer by Emmanuel Obiani Akari, Ibrahim Ademola Fetuga, Olabode Thomas Olakoyejo, Manasseh Babale Shitta, Omotayo Oluwatusin, Joshua Kolawole Gbegudu, Antonio Marcos de Oliveira Siqueira

“… Computational fluid dynamics was applied in the prediction of the effect of inlet temperature on the drying time of fish in a cabinet rotary dryer. …”
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Real-World Temperature Data From the Gulf of Mexico: Seasonality and Effect of the Loop Current With an Accessible Hands-On Activity by Andrée L. Ramsey, Mary Carla Curran, Amy S. Bower

“…Because ocean temperature influences both the frequency and intensity of tropical storms and hurricanes over the ocean in general, and in the Gulf of Mexico specifically, tracking the position of the meandering Loop Current and its deep-reaching cargo of warm water improves weather prediction, and thus preparation for these extreme storms. …”
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Inversion-Based Face Swapping With Diffusion Model by Daehyun Yoo, Hongchul Lee, Jiho Kim

“…This embedding vector serves as a crucial condition in the diffusion inversion process, facilitating the prediction of noisy images. Subsequently, the predicted noisy image undergoes processing using a pretrained ID conditional DDPM for face swapping. …”
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A machine learning based classifier for topological quantum materials by Ashiqur Rasul, Md Shafayat Hossain, Ankan Ghosh Dastider, Himaddri Roy, M. Zahid Hasan, Quazi D. M. Khosru

“…Abstract Prediction and discovery of new materials with desired properties are at the forefront of quantum science and technology research. …”
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Review of Fast Solar Jets and Coronal Mass Ejections by Sima Zeighami, Ehsan Tavabi

“…Currently, it is only possible to predict a magnetic storm 30 to 60 minutes before it occurs, which is a very short time. …”
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A Modified Model for Deflection Calculation of Reinforced Concrete Beam with Deformed GFRP Rebar by Minkwan Ju, Hongseob Oh, Junhyun Lim, Jongsung Sim

“…For better prediction of the moment-deflection relationship until the ultimate strength is reached, a nonlinear parameter (k) was also considered. …”
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Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty by Qinghua Wei, Yuanhao Wang, Guo Yang, Tianyuan Li, Shuting Yu, Ziqiang Dong, Tong-Yi Zhang

“…The present work systematically analyzes the important role of experimental uncertainty in machine learning, especially in the global optimization for material design, which demands high generalizability of predictions.…”
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Real-Time and In Situ Evaluation of Phycocyanin Concentration in Spirulina platensis Cultivation System by Using Portable Raman Spectroscopy by Yong He, Xiaoxi Liu, Hui Fang, Jinnuo Zhang, Xuping Feng

“…The least squares support vector machine model based on the characteristic peaks was used to estimate the concentration of phycocyanin and obtained good results with a correlation coefficient of prediction of 0.907 and residual predictive deviation of 3.357. …”
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Characterizing Auroral‐Zone Absorption Based on Global Kp and Regional Geomagnetic Hourly Range Indices by R. A. D. Fiori, L. Trichtchenko, C. Balch, E. Spanswick, S. Groleau

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Investigation of Burn Cut Parameters and Model for One-Step Raise Excavation Based on Damage Evolution Mechanisms by Kai Liu, Jiadong Qiu

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The Influence of Amplitude- and Frequency-Dependent Stiffness of Rail Pads on the Random Vibration of a Vehicle-Track Coupled System by Kai Wei, Pan Zhang, Ping Wang, Junhua Xiao, Zhe Luo

“…Considering that these frequencies of 65–150 Hz are the dominant frequencies of ground vibration accelerations caused by low-speed railway, the nonlinear amplitude- and frequency-dependent stiffness of rail pads should be taken into account in prediction of environment vibrations due to low-speed railway.…”
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Analysis and Optimization of the Vibration and Noise of a Double Planetary Gear Power Coupling Mechanism by Weijian Zhou, Yanyan Zuo, Mingyin Zheng

“…Furthermore, based on the vibration displacement of the housing surface, a prediction model of housing radiating noise is established. …”
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A tabular data generation framework guided by downstream tasks optimization by Fengwei Jia, Hongli Zhu, Fengyuan Jia, Xinyue Ren, Siqi Chen, Hongming Tan, Wai Kin Victor Chan

“…Through extensive experiments conducted on real-world tables with explicit column constraints and tables without explicit column constraints, we have demonstrated that TDGGD ensures increasing data volume while enhancing prediction accuracy. To the best of our knowledge, this is the first instance of deploying downstream information into a diffusion model framework.…”
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Reinforced Cost-Sensitive Graph Network for Detecting Fraud Leaders in Telecom Fraud by Peiwen Gao, Zhihua Li, Dibin Zhou, Liang Zhang

“…The model first constructs a graph from users’ call detail records (CDR) and then generates predictions using three base classifiers: GCN, GAT, and GraphSAGE. …”
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Machine learning techniques for non-destructive estimation of plum fruit weight by Atefeh Sabouri, Adel Bakhshipour, Mehrnaz Poorsalehi, Abouzar Abouzari

“…In this study, we addressed the problem of predicting plum FW using artificial intelligence (AI) methods based on fruit dimensions. …”
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Revised direct bandgap and band parameters for AlP: hybrid-functional first-principles calculations vs experiment by Cónal Murphy, Eoin P. O’Reilly, Christopher A. Broderick

“…Critically, using hybrid-functional first-principles calculations, we find that the Γ6c–Γ8v bandgap is ∼1 eV larger than the widely assumed value of 3.63 eV. This prediction is validated by using interband transition energies obtained from the hybrid-functional band structure to perform a constrained fit to spectroscopic ellipsometry data from the literature. …”
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Collaborative forecasting management model for multi‐energy microgrid considering load response characterization by Huiyu Bao, Yi Sun, Jie Peng, Xiaorui Qian, Peng Wu

“…The model combines a multi‐energy load prediction model with a management model based on deep reinforcement learning. …”
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Characterization of Various Plant-Produced Asphalt Concrete Mixtures Using Dynamic Modulus Test by Muhammad Irfan, Asad S. Waraich, Sarfraz Ahmed, Yasir Ali

“…Furthermore, two dynamic modulus prediction models, namely, Witczak and Hirsch, were evaluated for their regional applicability. …”
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A Review of Non-Uniform Load Distribution and Solutions in Data Centers: Micro-Scale Liquid Cooling and Large-Scale Air Cooling by Yifan Li, Congzhe Zhu, Xiuming Li, Bin Yang

“…The existing issues concerning the structure universality of the microchannel heat sink (MCHS), the stability of flow boiling and the new coolant, the prediction of local hot spots, and the intelligent control of the cooling system are identified. …”
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A Combined Model for Simulating the Spatial Dynamics of Epidemic Spread: Integrating Stochastic Compartmentalization and Cellular Automata Approach by Murad Bashabsheh

“…They consist of rather separate cells in one or multi-dimensional space, where each cell has a constant number of neighbors. Since CA can predict the geographic distribution of some epidemics through proper mathematical models, they have the potential of improving epidemic prediction and preventive measures in public health management. …”
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