Semi-Supervised Learning via Cross-Prediction-Powered Inference for Wireless Systems by Houssem Sifaou, Osvaldo Simeone

“…Semi-supervised learning leverages unlabeled samples to augment the available dataset by assigning synthetic labels obtained via machine learning (ML)-based predictions. However, treating the synthetic labels as true labels may yield worse-performing models as compared to models trained using only labeled data. …”
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Accelerating Energy-Efficient Federated Learning in Cell-Free Networks With Adaptive Quantization by Afsaneh Mahmoudi, Ming Xiao, Emil Bjornson

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GenAI-Based Models for NGSO Satellites Interference Detection by Almoatssimbillah Saifaldawla, Flor Ortiz, Eva Lagunas, Abuzar B. M. Adam, Symeon Chatzinotas

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Self‐Supervised Pre‐Training and Few‐Shot Finetuning for Gas‐Bearing Prediction by Long Han, Xinming Wu, Renjie Chen, Yunhua Shi, Zhanxuan Hu, Huijing Fang

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Deep Fusion Intelligence: Enhancing 5G Security Against Over-the-Air Attacks by Mohammadreza Amini, Ghazal Asemian, Burak Kantarci, Cliff Ellement, Melike Erol-Kantarci

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ORANSight-2.0: Foundational LLMs for O-RAN by Pranshav Gajjar, Vijay K. Shah

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Applying ANFIS and LSSVM Models for the Estimation of Biochar Aromaticity by Ganggang Pan, Haoyan Dong, Maryam Karimi Nouroddin

“…The main aim of this work is the determination of aromaticity in biochar from easier accessible parameters (e.g., elemental composition). To this end, two machine learning models, including adaptive neurofuzzy inference system (ANFIS) and least-squares support vector machine (LSSVM), were used to predict this constant form 98 dataset gathered from earlier reported sources. …”
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Reduced-Order Models and Conditional Expectation: Analysing Parametric Low-Order Approximations by Hermann G. Matthies

“…Similarly, in the field of machine learning, a function mapping the parameter set to the image space of the machine learning model is learned from a training set of samples, typically minimising the mean square error. …”
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Statistical analysis of sizing features of dust generated under the mechanical metal-working by N. N. Azimova, E. N. Ladosha, S. N. Kholodova, D. S. Tsymbalov, O. V. Yatsenko

“…The work objective was to develop mathematical methods for correct averaging of the size and mass parameters of dust under the solid metal machining.Materials and Methods. …”
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Analysis of Muscular Electrical Activity and Blood Perfusion of Upper Extremity in Patients with Hemiplegic Shoulder Pain: A Pilot Study by Minghong Sui, Naifu Jiang, Luhui Yan, Chenxi Zhang, Jiaqing Liu, Tiebin Yan, Guanglin Li

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Nonlocality in quantum cloning states by Jun Liu, Zhiwen Mo

“…Our results demonstrate that within specific operational ranges of the cloning machine parameters, the two-qubit reduced states are suitable for quantum teleportation but do not exhibit violations of Bell-CHSH inequalities. …”
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AutoML based workflow for design of experiments (DOE) selection and benchmarking data acquisition strategies with simulation models by Xukuan Xu, Donghui Li, Jinghou Bi, Michael Moeckel

“…Trade-offs in resource allocation strategies, in particular between identical replication of data points for statistical noise reduction and broad sampling for maximum parameter space exploration, and their impact on subsequent machine learning analysis are systematically investigated. …”
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Research on adaptive motion methods of flexible knee joints based on the artificial potential field by LUO Tianhong, LI Chaoyang, MA Xiangyu, FU Qiang, FANG Shangchen

“…ObjectiveConsidering the tracking error of the motion trajectory of the flexible knee joint and the influence of the flexibility on the joint motion, an adaptive impedance control method based on the artificial potential field (APF) was proposed.MethodsThe method took the pneumatic artificial muscle as the power source, and by establishing a kinetic model between the human-machine interaction moment and the knee joint motion angular velocity, the size of the impedance control parameter could be adjusted in real time, so as to realize the following of the motion of the exoskeleton knee joint and the human leg; the control parameter was optimized using the APF concept to enhance the effect of the motion following, and the effectiveness of the algorithm was verified by simulation and test.ResultsThe results show that the proposed APF-based adaptive impedance control method enables the exoskeleton to adaptively track the human motion trajectory and can reduce the error of trajectory tracking, thus improving the suppleness of the flexible knee joint control and enhancing the human-machine synergy of the system.…”
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Parametric Optimization of Viscoplastic Bars Under Dynamic Axial Loading by E. Cegielski, M. Życzkowski

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Parametric Characterization of a Tractor Engine by Specific Fuel Consumption by S. N. Devyanin, A. V. Bizhaev, Y. D. Pavlov, S. M. Vetrova, A. S. Barchukova

“…The paper highlights that equipping agricultural mobile machines with sensors and electronic controls enables the remote acquisition of real-time information regarding the technical condition of engine systems while operation. …”
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Ridge regression and its applications in genetic studies. by M Arashi, M Roozbeh, N A Hamzah, M Gasparini

“…When multicollinearity exists in the data set with outliers, we consider a robust ridge estimator, namely the rank ridge regression estimator, for parameter estimation and prediction. On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. …”
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The Effect of Chiller and Hot Runner Temperature on Appearance of 100 mL Pet Bottle Products Through the Stretch Blow Molding Process by Moh. Hartono, Prihadi Mulya Pradana

“…This machine has a high level of precision so that the aspects of strength and appearance quality on the packaging bottle are the main assessment. …”
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Convolutional neural network analysis of optical texture patterns in liquid-crystal skyrmions by J. Terroa, M. Tasinkevych, C. S. Dias

“…In this study, we demonstrate that the optical signatures of skyrmions can be utilised effectively in machine learning to predict important system parameters. …”
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滚齿机数控系统零编程技术的研究 by 舒启林, 蒋广玉, 侯傲

“…NC hobbing machine slams the complex transmission system of the ordinary hobbing machine.The digital control is adopted in each movement of the machine tool axis,the processing accuracy and efficiency of the machining are improved.In the hobbing processing,the specific kinematic relationship between the workpiece and tool is determined according to the parameters of them.And the zero-programming mathematical model of cylindrical gear is established on the analysis of the feasibility study of zero-programming technology,and it plays a crucial role in the zero-programming software development based on IPC+PMAC.The operators don’t need programming and only need to enter related parameter,the software will automatically generate gear processing program in the development system.…”
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基于机器视觉的齿轮参数测量系统设计 by 王文成

“…Aiming at the problem of gear parameter measurement,a new measurement method based on machine version is proposed.The framework of system and the functions of components are introduced,a study focused on digital image acquisition,image preprocessing and image segmentation technology are carried out,a method of gear center localization and gear teeth number counting based on mathematical morphology is proposed.On the base of that,other parameters are obtained by formula counting.The method is simple and does not need edge detecting.Experiment shows that the system is stable and fast,and it can meet the requement of gear parameter measurement.…”
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