Evaluation of labor ergonomics of machine milking operators working at milking machines «Carousel» by Yu. A. Tsoy, V. V. Kirsanov, R. A. Mamedova

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Detection of Transformer Faults: AI-Supported Machine Learning Application in Sweep Frequency Response Analysis by Hakan Çuhadaroğlu, Yılmaz Uyaroğlu

“…In this context, Sweep Frequency Response Analysis (SFRA) has emerged as an effective method for detecting potential faults at an early stage by examining the frequency responses of transformers. …”
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High-Frequency Cryptocurrency Price Forecasting Using Machine Learning Models: A Comparative Study by Fátima Rodrigues, Miguel Machado

“…Existing forecasting methods often struggle with the inherent non-stationarity and complexity of cryptocurrency price dynamics. …”
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Utilizing Machine Learning and Deep Learning for Precise Intensity-Duration-Frequency (IDF) Curve Predictions by Sheeraz Majeed Ameen, Shuokr Qarani Aziz, Anwer Hazim Dawood, Azhin Tahir Sabir, Dara Muhammad Hawez

“…This study adopts a comparative approach to estimate IDF curves using a combination of traditional statistical methods, machine learning techniques, and advanced deep learning models. …”
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An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

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Data analysis methods in astronomic objects classification (Sloan Digital Sky Survey DR14) by V. A. Golov, D. A. Petrusevich

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A novel directional pilot protection method for EHV transmission lines based on S-transform and SVM by Zhenwei Guo, Yingcai Deng, Tong Zhang, Zebo Huang

“…., fault resistance and fault angle, this paper proposes a novel directional pilot protection method. By studying the propagation of fault TW on transmission lines, the relationship between the energy of the transient voltage components and the fault direction is established. …”
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A single flow detection enabled method for DDoS attacks in IoT based on traffic feature reconstruction and mapping by Lixia XIE, Bingdi YUAN, Hongyu YANG, Ze HU, Xiang CHENG, Liang ZHANG

“…To address the slow response time of existing detection modules to Internet of things (IoT) distributed denial of service (DDoS) attacks, their low feature differentiation, and poor detection performance, a single flow detection enabled method based on traffic feature reconstruction and mapping (SFDTFRM) was proposed.Firstly, SFDTFRM employed a queue to store previously arrived flow based on the first in, first out rule.Secondly, to address the issue of similarity between normal communication traffic of IoT devices and DDoS attack traffic, a multidimensional reconstruction neural network model more lightweight compared to the baseline model and a function mapping method were proposed.The modified model loss function was utilized to reconstruct the quantitative feature matrix of the queue according to the corresponding index, and transformed into a mapping feature matrix through the function mapping method, enhancing the differences between different types of traffic, including normal communication traffic of IoT devices and DDoS attack traffic.Finally, the frequency information was extracted using a text convolutional network and information entropy calculation and the machine learning classifier was employed for DDoS attack traffic detection.The experimental results on two benchmark datasets show that SFDTFRM can effectively detect different DDoS attacks, and the average metrics value of SFDTFRM is a maximum of 12.01% higher than other existing methods.…”
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A Mechanical Fault Identification Method for On-Load Tap Changers Based on Hybrid Time—Frequency Graphs of Vibration Signals and DSCNN-SVM with Small Sample Sizes by Yanhui Shi, Yanjun Ruan, Liangchuang Li, Bo Zhang, Yichao Huang, Mao Xia, Kaiwen Yuan, Zhao Luo, Sizhao Lu

“…Therefore, a novel small-sample-size OLTC mechanical fault identification method incorporating short-time Fourier transform (STFT), synchrosqueezed wavelet transform (SWT), a dual-stream convolutional neural network (DSCNN), and support vector machine (SVM) is proposed. …”
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Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz by Mohammud Z. Bocus, Afzal Lodhi

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A Multilevel and Hierarchical Approach for Multilabel Classification Model in SDGs Research by Berliana Sugiarti Putri, Lya Hulliyyatus Suadaa, Efri Diah Utami

“…This study aimed to implement and evaluate problem transformation methods and machine learning classification algorithms with a multilevel and hierarchical approach to categorize research publications into SDG levels. …”
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Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension by Yuyang Gao, Pengyue Ma, Jiahua Pan, Hongbo Yang, Tao Guo, Weilian Wang

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Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results by Gražina KORVEL, Olga KURASOVA, Bożena KOSTEK

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Method of determining power and mathematical modeling of physical processes in testing traction induction motors by mutual loads by Viktor Vasilevich Kharlamov, Denis Igorevich Popov, Artyom Valerevich Litvinov

“…To refine the mathematical model proposed to use the method of determining the dependency of the losses in the elements of frequency converters, located in the structure of the scheme of mutual loads of induction motors, the magnitude of the consumed and generated power of test and load machine.…”
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Electrical Fault Diagnosis Method for Tunneling Equipment Based on Fault Simulation and Optimized Particle Swarm Algorithm by Huan Zou, Xueping Zhang, Xin Wang, Yu Li

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Analysis of the account of slot harmonics in stator’s EMF in mathematical modeling of the process of testing induction motors by the mutual load method by V. V. Kharlamov, D. I. Popov

“…It is shown that the spectrum-current analysis method can be used to determine rotation speed of induction machines when they are tested by the mutual load method using various schemes. …”
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A novel seismic inversion method based on multiple attributes and machine learning for hydrocarbon reservoir prediction in Bohai Bay Basin, Eastern China by Zongbin Liu, Jianmin Zhu, Bo Tian, Rui Zhang, Yongheng Fu, Yuan Liu, Lixin Wang

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MODELING OF THE MACHINE FOR THE BALANCING OF THE ROTOR IN THE ANSYS SOFTWARE COMPLEX by I. R. Tazeyev, S. O. Gaponenko, A. E. Kondratiev, A. N. Zamaliev

“…The Autodesk Inventor CAD software was used for modeling of the balancing machine and the rotor. The modal analysis was conducted by using the block method of Lanczos on the basis of the ANSYS system. …”
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Predicting low ionospheric parameters and low frequency sky wave propagation strength using machine learning by Jian Wang, Chengsong Duan, Qiao Yu, Cheng Yang

“…Therefore, to enhance the predicting accuracy of LF sky wave propagation, we proposed an improved method based on the machine learning method. Firstly, we employed a machine learning method to create a prediction model for the critical frequency of the low ionospheric E layer (f oE), which significantly affects LF sky wave propagation. …”
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Frequency Response Function-Based Finite Element Model Updating Using Extreme Learning Machine Model by Yu Zhao, Zhenrui Peng

“…The proposed FEMU method is feasible.…”
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