Bionic Design for Column of Gantry Machining Center to Improve the Static and Dynamic Performance by Shihao Liu, Wenhua Ye, Peihuang Lou, Weifang Chen, Jungui Huang, Lili Xiao

“…The bionic design method was used to improve column structure of the gantry machining center, and three kinds of bionic columns were put forward. …”
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Machine Learning‐Driven Surrogate Modeling for Optimization of Triboelectric Nanogenerator Design Parameters by Mohammad Abrar Uddin, Myeongju Lim, Rubiga Kim, Barrett London Burgess, Ken Roberts, Junghyun Kim, Taeil Kim

“…To address this problem, this study takes four process parameters such as thickness, pore ratio, applied force, and frequency into account and leverages advanced design methods (e.g., Design of Experiment) and machine learning‐based regression models to systematically explore the design space. …”
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Analysis of the development of electric drives for oil rocking machines by the results of patent search by I. V. Ivshin, A. R. Safin, R. R. Gibadullin, T. I. Petrov, A. N. Tsvetkov, M. F. Nizamiyev, V. Yu. Kornilov

“…Field of application: electrical equipment for oil pumping units.The purpose of the work is to identify inventions in the field of electric drives based on Russian highly efficient synchronous motors for oil pumping machines, to determine the advantages and disadvantages of modern developments in this field.Methods. …”
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Performance of 5G Slicing With Access Technologies and Diversity: A Review and Challenges by Sinta Novanana, Adrian Kliks, Ajib Setyo Arifin, Gunawan Wibisono

“…In this paper, the classification of 5G slicing methods is comprehensively explained such that the correlations among slicing, access technologies, and diversity are well defined and identified according to the characteristics of each service. …”
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Prestress Assisted Machining: Achieving high surface integrity in thin wall milling by Álvaro Sáinz de la Maza García, Luis Norberto López de Lacalle Marcaide, Gonzalo Martínez de Pissón Caruncho

“…This method, consists on externally applying an initial stress state to the workpiece during machining. …”
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Metering Automation System 3.0 Base Version Based on Machine Learning by Sheng Li, Leping Zhang, Hang Dai, Lukun Zeng, Yuan Ai, Shuang Qi, Yuanzhai Cui

“…However, traditional machine learning methods and standalone deep learning architectures struggle to balance spatiotemporal feature extraction, computational efficiency, and deployment constraints for high-frequency multivariate metering data. …”
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Applications of machine learning in potentially toxic elemental contamination in soils: A review by Yan Li, Bao Xiang, Tianyang Wang, Yinhai He, Xiaoyang Liu, Yancheng Li, Shichang Ren, Erdan Wang, Guanlin Guo

“…Traditional investigational methods are often inadequate for large-scale assessments because they are time-consuming, costly, and have a limited accuracy. …”
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Remote Sensing Drought Monitoring and Assessment in Southwestern China based on Machine Learning by Hejia JIA, Xiehui LI, Lei WANG, Yuting XUE, Huiquan LIN

“…Due to the complexity of drought and the diversity of influencing factors， the accurate monitoring of drought still faces many problems， especially the increasing frequency and aggravation of drought in Southwestern China， and the formation and disaster causing process have certain particularity.However， the traditional drought monitoring methods cannot meet the requirements of regional drought monitoring， so more scientific monitoring methods and means are needed.Since machine learning can comprehensively consider a variety of disaster causing factors to establish a comprehensive drought monitoring model， it undoubtedly provides a new technical means for drought monitoring.Therefore， this paper used multi-source remote sensing data from 2010 -2019 and meteorological station data from 1980-2019 to first construct a random forest monitoring model to reconstruct and supplement the surface temperature in Southwestern China， and then constructed XGBoost monitoring model to monitor， evaluate and validate the drought in Southwestern China.The results showed that： （1） The correlation coefficients between the training set and test set of the random forest model and the actual surface temperature of the stations exceeded 0.9， which reached a significant correlation.The spatial distribution of LST reconstruction values was similar to that of remote sensing monitoring values， and the values were close to the observed values of meteorological stations.（2） The correlation coefficients between the monitoring values of XGBoost model training set and test set and the SPEI calculated values at the stations were more than 0.86， with significant correlation.The overall consistency rate of drought grade between the monitored value and the calculated SPEI values exceeded 85%.（3） The overall consistent rate between the monitored values of the XGBoost model and the MCI values was above 67.88%， which was more consistent.The consistent rate of all months exceeded 58%， with the highest consistent rate of 75.07% in September and the lowest consistent rate of 58.26% in February.（4） The drought in each season monitored by the model was basically consistent with the actual drought， which could better reflect the spatial distribution and drought in Southwestern China.…”
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An Objective and Subjective Study of Noise Exposure within the Frequency Range from 10 kHz to 40 kHz by Bożena SMAGOWSKA

“…The questionnaire survey of annoyance high frequency noise (i.e. in the audible frequency and low ultrasound range) was conducted among 52 operators of machines. …”
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Analysis of noise generated by wind turbines with reference to other low frequency noise sources and their possible impact on human health by Andrzej Staniek, Magdalena Miterska

“…In order to properly identify low frequency noise sources apart from measurement systems for registering sound signals vibration methods might be utilized. …”
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Applying EQTransformer to laboratory earthquakes: detecting and picking acoustic emissions with machine learning by Jack Sheehan, Qiushi Zhai, Lindsay Yuling Chuang, Timothy Officer, Yanbin Wang, Lupei Zhu, Zhigang Peng

“…Recently, automatic methods based on machine learning (ML) or template matching have been applied to detect AE events. …”
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Hybrid Method for Point Cloud Classification by Abdurrahman Hazer, Remzi Yildirim

“…In this study, we introduce a novel hybrid ResPOL method that integrates a bidirectional architecture with a newly developed Patch-Offset Lambda (POL) mechanism for feature extraction from point cloud data. …”
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Energy-Based Reinterpretation of Equal Area Criterion for Generator Instability Assessment via Local Rotational Speed and Voltage Frequency Measurements by Jongju Kim

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A large dataset for VEP based brain-computer interfaces employing narrow-band code modulation and frequency-phase modulation by Li Zheng, Sen Tian, Yida Dong, Weihua Pei, Xiaorong Gao, Yijun Wang

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Background for modeling the dynamic characteristics of advanced spacecraft drives considering the operation of oscillators by A. N. Sova, M. I. Stepanov, V. A. Sova, A. I. Bykov

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Aspect Based Sentiment Analysis on Shopee Application Reviews Using Support Vector Machine by Dyah Ayu Wulandari, Fitra A. Bachtiar, Indriati Indriati

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Vibration Characteristics of Double-Shield TBM Cutterhead Under Rock–Machine Interaction Excitation by Guang Zhang, Qing Song, Qiuming Gong, Dongxing Liu, Dongwei Li, Minghao Sun

“…During the tunneling process of a double-shield TBM, vibrations generated by rock–machine interaction can affect its safe, efficient, and stable operation. …”
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ECG Biometrics on Mobile Devices: High-Accuracy Authentication Using i-Vectors and Cepstral Coefficients by F. Saba Kockan, Bulent Bolat

“…Performance metrics obtained from the Heartprint dataset—namely, 94.39% accuracy, 93.17% true acceptance rate (TAR), and 5.61% false acceptance rate (FAR)—demonstrate that the i-vector-based approach yields results on large datasets that are comparable to those achieved by deep learning and conventional machine learning methods. The use of a brief 5-second ECG signal minimizes memory and processing power requirements, enabling rapid data processing and real-time authentication. …”
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Numerical Simulation of Ambiguity Resolution in Multiple Information Streams Based on Network Machine Translation by Lei Wang, Qun Ai

“…Using the naive Bayesian machine learning method and the feature vector set extracted and constructed by the Dice coefficient method, a semantic word disambiguation model based on semantics is realized. …”
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Innovative Application of Statistical Sound Analysis for Fault Diagnosis in Variable-Speed Induction Machines by El Idrissi Abderrahman, Derouich Aziz, Mahfoud Said, El Ouanjli Najib, Chojaa Hamid, Chantoufi Ahmed

“…The article presents an innovative method leveraging statistical sound analysis to diagnose malfunctions in variable-speed drive-controlled (VSD) induction machines (IM). …”
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