用于糖衣机的非正交锥齿轮设计 by 黄大宇, 付晓莉

“…Through adding a orthogonal bevel gearpair,traditional type of coating machine is advanced.The design work of non-orthogonal bevel gears of coating machine includes calculation of the geometric parameters,Calculation of bending fatigue strength and contact fatigue strength.That design overcomes shortcomings of structure bulkiness,installation inconvenience and working unsteadiness from the leaning setting of traditional speed reducer.…”
Get full text

锥面包络圆柱蜗杆失配啮合传动 by 陈坚兴, 汤宏武, 张光辉

“…A type of ZK-worm gearing with ZA-worm wheel in the state of mismatched point contact ispresented. A method to machine and modify the toothprofile of the worm by adjusting parameters for machine tool setting and cutter is proposed. …”
Get full text

Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The article analyzes Russian and foreign bibliography on the research problem. Consideration of machine learning methods for detecting and correcting outliers in time series is proposed. …”
Get full text

Evaluation of braze welded joints using the ultrasonic method by Ulbrich Dariusz, Jezierski Jakub, Josko Marian, Banas Piotr

Get full text

Bending cyclic behavior and scatter-band analysis of aluminum alloys under beneficial and detrimental conditions through high-cycle fatigue regime by Mohammad Azadi, Hanieh Aroo

“…Then, the second sensitive parameter was demonstrated as the pre-corrosion, which caused significant degradation of fatigue properties in the material. …”
Get full text

LOW ALLOY STEEL SHAFT SURFACE REGENERATIVE WELDING WITH MICRO-JET COOLING by Bożena SZCZUCKA-LASOTA, Tomasz WĘGRZYN, Krzysztof LUKASZKOWICZ

“…Substantial information about parameters of steel machine elements surfacing with the micro-jet cooling process was given. …”
Get full text

The influence of the harvester manipulator design characteristics on the working area optimal size by Lagerev A.V., Makulina A.V., Lagerev I.A.

“…The geometric parameters of the implemented working area are determined by the working position of the machine in the appropriate technological mode, that is, the place of installation of the machine relative to the tree or group of trees to be harvested. …”
Get full text

串联盘输送机输送系统的动态分析 by 栾丽君, 付艳梅, 刘玉刚

“…On the basic of the machine’s structure,the mechanical model of damp dynamic multi-degrees freedom is built,the system parameters are analysized and determined. …”
Get full text

Analysis of Meshing Contact Characteristics of the Gear Transmission System Based on Data Mining Technology by Li Shengjia, Ma Yali, Zhao Yongsheng, Pu Dajun, Yan Shidang

“…The correlation between system parameters and meshing contact characteristics is analyzed using the maximum information coefficient, which provides a candidate feature subset for the prediction model. …”
Get full text

PATTERN FORECASTING OF PERFORMANCE INDICES FOR AIR-AND-SCREEN CLEANER FROM CHAFFING EFFICIENCY RISE by Yury Ivanovich Yermolyev, Andrey Vladimirovich Butovchenko, Artem Alexandrovich Doroshenko

“…The obtained results have shown a s ignificant increase in productivity and technological parameters of the similar machine performance from the efficiency growth of their air separator.…”
Get full text

Human mobility is well described by closed-form gravity-like models learned automatically from data by Oriol Cabanas-Tirapu, Lluís Danús, Esteban Moro, Marta Sales-Pardo, Roger Guimerà

“…At the other end, we have machine learning models, with tens of features and thousands of parameters, which predict mobility more accurately than gravity models but do not provide clear insights on human behavior. …”
Get full text

An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach by Ibrahim Delibalta, Lemi Baruh, Suleyman Serdar Kozat

“…Based on these observations, machine learning algorithms produce digital interventions such as targeted advertisements or tweets. …”
Get full text

Hyperparameter Optimization EM Algorithm via Bayesian Optimization and Relative Entropy by Dawei Zou, Chunhua Ma, Peng Wang, Yanqiu Geng

“…Hyperparameter optimization (HPO), which is also called hyperparameter tuning, is a vital component of developing machine learning models. These parameters, which regulate the behavior of the machine learning algorithm and cannot be directly learned from the given training data, can significantly affect the performance of the model. …”
Get full text

In-situ defect detection and material property evaluationin additive manufacturing using acoustic signal and machinelearning by Abdullah Bin Zainal, Zheng Jie Tan, Saritha Samudrala, Zi Wen Tham, Lei Zhang, Santhakumar Sampath

“…The results show that the machine learning models achieve an average material property estimation accuracy of 89%, highlighting its effectiveness in enhancing the monitoring process parameters. …”
Get full text

Automatic Optical Path Alignment Method for Optical Biological Microscope by Guojin Peng, Zhenming Yu, Xinjian Zhou, Guangyao Pang, Kuikui Wang

Get full text

Sensor Monitoring of Conveyor Working Operation with Oscillating Trough Movement by Leopold Hrabovský, Štěpán Pravda, Martin Fries

“…Suitably designed rubber springs, of optimum stiffness, dampen the vibrations transmitted to the machine frame. From their sizes, it is possible to remotely monitor the working operation of the vibrating conveyor or to obtain information about the failure of one or several used rubber springs.…”
Get full text

Optimizing MRI Scheduling in High-Complexity Hospitals: A Digital Twin and Reinforcement Learning Approach by Fabián Silva-Aravena, Jenny Morales, Manoj Jayabalan, Paula Sáez

“…The digital twin simulates realistic hospital dynamics using parameters extracted from a MRI publicly available dataset, modeling patient arrivals, examination durations, MRI machine reliability, and clinical priority stratifications. …”
Get full text

Remote Sensing Retrieval Method Based on Few-Shot Learning: A Case Study of Surface Dissolved Organic Carbon in Jiangsu Coastal Waters, China by Jiahao Zhang, Huan Li, Yiyang Miao, Zeng Zhou, Huihua Lyu, Zheng Gong

“…The same spatial interpolation technique was applied to both in-situ observation data and reflectance data of multiple bands at corresponding locations, expanding the original data distribution, thus increasing the sample size and diversity to create a virtual dataset. Subsequently, the machine learning model learned the complex relationships between target parameters and multidimensional features using the virtual dataset, which was then applied to real remote sensing reflectance images to obtain retrieval results. …”
Get full text

Prediction of Anemia from Multi-Data Attribute Co-Existence by Talal Qadah, Asmaa Munshi

“…In this study, the most important contribution is that there isn’t a single machine learning method that can accurately predict anemia based on the parameters associated with anemia. …”
Get full text

Comparison of static friction and surface topography of low friction and conventional TMA orthodontic arch wires: An in-vitro study by Nouf Alsabti, Nabeel Talic

“…A surface roughness evaluation using a profilometer machine revealed that the highest mean of all three roughness parameters was found in the TMA-C group, followed by the TMA-Low and SS arch wires in descending order. …”
Get full text