Mathematical Modeling of High-Energy Shaker Mill Process with Lumped Parameter Approach for One-Dimensional Oscillatory Ball Motion with Collisional Heat Generation by Kwon Joong Son

“…Incorporating these thermal interactions allows the model to provide a more comprehensive depiction of the energy dynamics within the system, leading to more precise predictions of temperature changes. Utilizing a lumped parameter method, the study simplifies complex airflow dynamics and non-uniform temperature distributions in the milling system, enabling efficient numerical analysis. …”
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Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations by W. A. Bristow, C. A. Topliff, M. B. Cohen

“…Further it is found that the mean‐squared difference between predictions of the model and observed values of the velocity are substantially lower than the same quantity calculated for an existing climatology that was not formed with ML techniques.…”
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…This study shows that advanced machine learning models, particularly BNN and NODE, can predict pharmaceutical solubility and improve crystallization process design and optimization.…”
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An AI framework for counterattack detection and decision-making evaluation in football by Jiangyan Yang, Huanmin Ge, Yixiong Cui

“…Subsequently, a comprehensive approach integrating Transformer and Graph Neural Networks was employed to model and predict match event decisions based on prior match events and tracking data. …”
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Transductive zero-shot learning via knowledge graph and graph convolutional networks by Qiong Li, Xin Sun, Junyu Dong

“…During testing, a clustering strategy, the Double Filter Module with Hungarian algorithm, is applied to the unseen samples, and then, the learned classifiers are used to predict their categories. …”
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FRESH: Fusion-Based 3D Apple Recognition via Estimating Stem Direction Heading by Geonhwa Son, Seunghyeon Lee, Yukyung Choi

“…Secondly, we designed a 3D detection algorithm that not only recognizes the dimensions and location of apples, as existing methods do, but also predicts their 3-axis rotation. …”
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Shoe configuration effects on equine forelimb gait kinetics at a walk by Rita Aoun, Zaneta Ogunmola, Anaïs Musso, Takashi Taguchi, Catherine Takawira, Mandi J. Lopez

“…A random forest classifier algorithm was used to predict shoeing condition from kinetic outcome measures. …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. …”
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Integrative analysis of epigenetic subtypes in acute myeloid Leukemia: A multi-center study combining machine learning for prognostic and therapeutic insights. by Jincan Li, Shengyue Wang

“…Drug sensitivity was predicted using the pRRophetic algorithm with GDSC database reference.…”
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PRICE ESTIMATION OF LIMIT ORDER WITH HIGH EXECUTION PROBABILITY by I. O. Morozov, S. A. Pottosina

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SHOCK PULSE REPETITION FREQUENCY ESTIMATION BY PERIODIC WAVELET TRANSFORM by I. G. Davydov, S. U. Vasiukevich, A. V. Tsurko, I. M. Segliuk

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Identification of Outer Galaxy Cluster Members Using Gaia DR3 and Multidimensional Simulation by Vishwas Patel, Joseph L. Hora, Matthew L. N. Ashby, Sarita Vig

“…The more accurately predicted simulation distance estimates closely agree, within uncertainty limits, with the median distance estimates derived from Gaia data, and are compared with the kinematic distances from the Wide-field Infrared Survey Explorer H ii survey.…”
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Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

“…HPE, crucial in applications like sports analysis and surveillance systems, involves predicting human joint locations from images and videos. …”
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Proposing a New Method for Customer Segmentation Based on Their Level of Loyalty and Defining Appropriate Strategies for Each Segment by Samira KHodabandehlou, Ali Akbar Niknafs

“…The obtained data have been analyzed using Clementine 14.2 software application using MLP and RBF neural networks as well as the K-means algorithm. The results of the study show that the proposed method provides the highest level of accuracy for predicting the customers’ loyalty. …”
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A novel re-entrant circular star-shaped auxetic honeycomb with enhanced energy absorption and anisotropic Poisson’s ratio by Danrong Shi, Zhuangzhuang Wang, Yongwei Li, Ruyuan Huo, Jin Zhang, Jianguo Cai

“…A theoretical framework based on plastic dissipation was developed to predict the plateau stresses, and the influence of key geometric parameters on deformation modes and energy absorption was systematically examined. …”
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An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment by Julian R. Rice, G. Andrew Fricker, Jonathan Ventura

“…Specifically, we develop and train a novel PointNet-based neural network architecture to predict tree locations directly from LiDAR data augmented with multi-spectral imagery. …”
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Integrated Simulation Process Chain: From 3D Roll Forming Design to Crash Analysis by Sedlmaier Albert, Dietl Thomas, Abee André, Harrasser Johann, Pereira Miguel Sousa

“…This holistic approach enhances the fidelity of product performance predictions, offering a robust framework for optimizing forming processes and end-use structural integrity.…”
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Optimal Report Strategies for WBANs Using a Cloud-Assisted IDS by Shigen Shen, Keli Hu, Longjun Huang, Hongjie Li, Risheng Han, Qiying Cao

“…Experiments show the effectiveness of the dynamic multistage IDSRG in predicting the type and optimal strategy of a malicious body sensor.…”
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Inverse Identification of Constituent Elastic Parameters of Ceramic Matrix Composites Based on Macro–Micro Combined Finite Element Model by Sheng Huang, Le Rong, Zhuoqun Jiang, Yuriy V. Tokovyy

“…A BP neural network was used to predict the multiscale stiffness, considering the influence of the porous structure on the macroscopic stiffness of the material. …”
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Enhancement of joint quality for laser welded dissimilar material cell-to-busbar joints using meta model-based multi-objective optimization by Andreas Andersson Lassila, Tobias Andersson, Rohollah Ghasemi, Dan Lönn

“…Artificial neural network-based meta models, trained on numerical results from computational fluid dynamics simulations of the laser welding process, are used to predict and evaluate the joint quality. A set of optimized process parameters is identified, in order to simultaneously maximize the interface width for the joints, and minimize the formation of undercuts and in-process temperatures. …”
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