CALCULATION SPECIFICATION OF ACOUSTIC SCREENS LOCATED IN PRODUCTION AREA by Veronika Alexandrovna Bondarenko, Igor Vladimirovich Boguslavskiy, Sergey Sergeyevich Podust

Get full text

Compensation of the Radial Error of Measuring Head based on Forming Grinding Machine by Wang Zhonghou, Cao Huan, Li Gang, Liu Xingrong

“…According to the principle of polar coordinates measuring and tooth profile deviation calculation,an optimization model with purpose of minimum tooth profile and variable parameter of radial error is established based on the object of standard involute spur gear.After resolving this radial error and compensating the machine with the error,a helical involute gear is measured and the measured result is compared with the testing result of the three coordinate of the testing results of the three coordinate measuring instrument,the rationality of the radial error solving of the measuring head is obtained.…”
Get full text

Research on Machine Semantic Recognition in Different Bel Canto Music Backgrounds by Feng Ke

“…Finally, this paper applies the Bel Canto semantic feature clustering method to multicomponent signal parameter estimation, uses the clustering method to cluster the time-frequency analysis of nonstationary signals, obtains the time-frequency distribution of each signal component, and then estimates the parameters of each single-component signal. …”
Get full text

Discrete Model Reference Adaptive Control System for Automatic Profiling Machine by Peng Song, Guo-kai Xu, Xiu-chun Zhao

“…Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. …”
Get full text

Stator Electrically-excited Brushless Synchronous Machine and Its Inductance Calculation by JIA Guanglong, CHEN Zhichu, HU Yongfeng, LI Weiye

“…It is known that the reliability of electrically excited synchronous machine with brush is reduced. It proposed a new type of electrically excited synchronous machine, the stator electrically-excited brushless synchronous machine (SEBSM). …”
Get full text

Uncertainty Quantification of Geophysical and Hydrologic Parameters Estimated From Borehole Nuclear Magnetic Resonance Data by Burke J. Minsley, Stephanie N. Phillips, Stephanie R. James

Get full text

NC MACHINE FAULT DIGNOSIS BADED ON LCD MULTI DISPERSION ENTROPY by LI MeiHong

“…In order to improve fault diagnosis effect of bearing used in NC machine, a fault feature extraction and diagnosis method of bearing based on LCD multi dispersion entropy was proposed. …”
Get full text

FAIRness Along the Machine Learning Lifecycle Using Dataverse in Combination with MLflow by Lincoln Sherpa, Valentin Khaydarov, Ralph Müller-Pfefferkorn

“…This poses novel challenges related to keeping the trained model Findable, Accessible, Interoperable and Reusable (FAIR), especially for the automation of the entire machine learning lifecycle within the concept of Machine Learning Operations (MLOps). …”
Get full text

Machine Learning to Assess Relatedness: The Advantage of Using Firm-Level Data by Giambattista Albora, Andrea Zaccaria

“…Our results show that relatedness is scale dependent: the best assessments are obtained by using machine learning on the same typology of data one wants to predict. …”
Get full text

A Novel SHiP Vector Machine for Network Intrusion Detection by Sowmya T., E. A. Mary Anita

“…In this paper, network intrusion detection is proposed using an improved version of the support vector machine model to detect DoS attacks. Here, the SVM model considers the weight parameter along with the kernel to find the best decision boundary that separates the data into DoS and normal. …”
Get full text

Multi-objective design optimisation of a delta coordinate measurement machine by Louw Jakobus Murray, de Ronde Willis, Marais Stephen, Maweni Thabisa

“…Employing the Non- dominated Sorting Genetic Algorithm II (NSGA-II) [1], the methodology aims to balance competing objectives like measurement accuracy, motion resolution, and machine size. Through an iterative process and simulation- guided parameter refinement, new Pareto optimal solutions are identified at concurrent decision-making steps to reach a final design solution. …”
Get full text

Lumped Parameter Model for Structural Analysis of Over-Constrained Multi-Legged Parallel Mechanism Supporting System Applied to Cryogenic Devices by Luca Piacentini, Luca Dassa, Diego Perini, Andris Ratkus, Toms Torims, Stefano Uberti

Get full text

Sensorless Deadbeat Control Strategy With Adaptive Capability for PMSM Drive Machines by Sadeq Ali Qasem Mohammed, Mohammad M. Almuhaini, Kyo-Beum Lee

Get full text

Amplitude and frequency of human gait synchronization with a machine oscillator system by Ryan T. Schroeder, James L. Croft, John E. A. Bertram

“…Here we systematically measure synchronization over a broad range of parameters in machine oscillations, applied vertically near the body center of mass during walking. …”
Get full text

Dynamic Modeling and Analysis of the Large-Scale Rotary Machine with Multi-Supporting by Xuejun Li, Yiping Shen, Songlai Wang

“…Axis line deflection is a vital parameter to determine mechanics state of rotary machine, thus body axial vibration needs to be studied for dynamic monitoring and adjusting of rotary machine. …”
Get full text

Machine Learning‐Assisted Pulse Electrodeposition of Copper for Enhanced Nitrate Sensing by Seyed Oveis Mirabootalebi, Annalise Mackie, Gideon Vos, Dr. Mostafa Rahimi Azghadi, Dr. Yang Liu

“…The electrode modification process that determines the sensing performance was investigated by machine learning approaches to understand the relationship between the sensors’ output and the copper deposition parameters. …”
Get full text

Application of machine learning in identifying risk factors for low APGAR scores by Haifa Fahad Alhasson, Nagat Elhag, Shuaa Saleem Alharbi, Ishag Adam

“…Methods This study aimed to develop a machine-learning model that predicts low APGAR scores by incorporating maternal, fetal, and perinatal factors in Wad Medani, Sudan. …”
Get full text

Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In data analysis, machine learning has already been applied as an alternative to traditional methods for signal detection, source localization, noise reduction, and parameter estimation. …”
Get full text

Learning Random Access Schemes for Massive Machine-Type Communication With MARL by Muhammad Awais Jadoon, Adriano Pastore, Monica Navarro, Alvaro Valcarce

“…We employ value decomposition networks (VDN) and QMIX algorithms with parameter sharing (PS) and compare their policies with the deep recurrent Q-network (DRQN). …”
Get full text

Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…However, traditional machine learning (ML) models often suffer from local optima and limited generalization ability when dealing with complex nonlinear problems, thereby compromising prediction accuracy and stability. …”
Get full text