Comparative Study of Machine Learning Techniques for Insurance Fraud Detection by Navin Duwadi, Anita Sharma

“…However, as strategies and methods for committing insurance fraud have evolved, the frequency and volume of such fraudulent activities have also increased. …”
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Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…The problem of predicting the reaction kinetics of acid systems by processing an array of laboratory data using machine learning methods, specifically linear regression and random forest methods, was discussed. …”
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Use of machine learning for simplification of University Personality Inventory (UPI) by Weihua Guo, Jinsheng Hu, Qi Qiang, Xianke Chen

“…And the four items of Sensitive emotions, Physical exhausted, Feel self-abased and Uneasy without reason have high stability, the frequency of occurrence is >90 %. Conclusion: The results indicate that machine learning can successfully be applied to simplify the UPI and may be applicable for simplifying other lengthy measurement tools. …”
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Novel Machine Learning-Based Brain Attention Detection Systems by Junbo Wang, Song-Kyoo Kim

“…Based on the characteristics of EEG signals, this research identifies the most effective method for detecting brain attention by adapting various preprocessing and machine learning techniques. …”
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Machine learning-driven strategies for enhanced pediatric wheezing detection by Hye Jeong Moon, Hyunmin Ji, Hyunmin Ji, Baek Seung Kim, Beom Joon Kim, Kyunghoon Kim, Kyunghoon Kim

“…To overcome these limitations, artificial intelligence models have been developed.MethodsIn this prospective study, we aimed to compare respiratory sound feature extraction methods to develop an optimal machine learning model for detecting wheezing in children. …”
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Recent advances in ultra-precision machining of lithium niobate crystals by Yebing TIAN, Chengwei WEI, Xiaomei SONG, Cheng QIAN

“…New technologies, such as high-shear and low-pressure grinding and magnetorheological shear thickening polishing, are the most promising methods for achieving ultra-precision machining of LiNbO3 crystals. …”
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Analysis of signals from air conditioner compressors with ordinal patterns and machine learning by Keila Barbosa, Alejandro C Frery, George DC Cavalcanti

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Multi-Spectral Optimization for Tissue Probing Using Machine Learning by Yarden Tzabari Kelman, Hadas Lupa Yitzhak, Nadav Shabairou, Shahaf Finder, Zeev Zalevsky

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Visual analysis of fruit harvesting machine based on CiteSpace by YANG Daorina, ZHANG Fengkui, WANG Yulong, HE Ruohong, ZHU Jikui, LI Ping

“…Through keyword analysis, it was found that high-frequency keywords such as “mechanical harvesting” and “machine vision” belonged to this field. …”
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TFSNet: A Time–Frequency Synergy Network Based on EEG Signals for Autism Spectrum Disorder Classification by Lijuan Shi, Lintao Ma, Jian Zhao, Zhejun Kuang, Sifan Wang, Han Yang, Haiyan Wang, Qiulei Han, Lei Sun

“…Traditional diagnosis methods rely on professional doctors to make subjective diagnosis through scales, the feature extraction of existing machine learning methods is inefficient, and existing deep learning methods have limitations in capturing time-varying features and the joint expression of time–frequency features. …”
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Modeling operation modes of hydraulic drives with frequency-throttle regulation of mobile transport and overloading ropes complexes by Lagerev A.V., Tarichko V.I., Lagerev I.A.

“…Specific design features, modes and conditions of their operation in comparison with traditional freight and passenger fixed-line cableways require the development of special design methods and design calculations for this type of machine. …”
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Privacy-Preserving Detection of Tampered Radio-Frequency Transmissions Utilizing Federated Learning in LoRa Networks by Nurettin Selcuk Senol, Mohamed Baza, Amar Rasheed, Maazen Alsabaan

“…LoRa networks, widely adopted for low-power, long-range communication in IoT applications, face critical security concerns as radio-frequency transmissions are increasingly vulnerable to tampering. …”
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COMPARATIVE EVALUATION OF THE FREQUENCY OF RISK FACTORS FOR THE DEVELOPMENT OF CORONARY HEART DISEASE AND ARTERIAL HYPERTENSION IN MINERS WITH ANTHRACOSILICOSIS by Николай Иванович Панев, Наталья Александровна Евсеева

“…Materials and methods. The study involved 269 workers of the main professions of coal mines (drifters, stope miners, mining machine operators): 139 miners with a previously proven diagnosis of anthracosilicosis, 130 miners of the control group (workers with long-term labor experience without lung pathology and occupational diseases). …”
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Research on Load Adaptive Control for High-Frequency Motion of Voice Coil Motor With Online Parameter Optimization by Feng Huang, Chenxi Wang, Qipeng Li

“…Experimental results show that compared with classical PID control and fuzzy PID adaptive control, the proposed control method enables the VCM to achieve higher motion accuracy during high-frequency motion. …”
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A Frequency-Shifting Variational Mode Decomposition-Based Approach to MI-EEG Signal Classification for BCIs by Haiqin Xu, Shahzada Ali Hassan, Waseem Haider, Youchao Sun, Xiaojun Yu

“…The FS-VMD method works by extracting and shifting the fundamental frequency of the EEG signal to a lower frequency range, followed by an iterative decomposition process that enhances signal clarity and reduces mode aliasing. …”
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Evaluation of the Influence of Lorentz Forces on the Natural Frequencies of a Dual-Microcantilever Sensor for Ultralow Mass Detection by Luca Banchelli, Georgi Todorov, Vladimir Stavrov, Borislav Ganev, Todor Todorov

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Real-Time Model Predictive Control for Two-Level Voltage Source Inverters with Optimized Switching Frequency by Ariel Villalón, Claudio Burgos-Mellado, Marco Rivera, Rodrigo Zuloaga, Héctor Levis, Patrick Wheeler, Leidy Y. García

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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. …”
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Decoding the footsteps of the African savanna: Classifying wildlife using seismic signals and machine learning by René Steinmann, Tarje Nissen‐Meyer, Fabrice Cotton, Frederik Tilmann, Beth Mortimer

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Fault Early Warning of Wind Turbine Gearbox Based on Machine Learning by CHEN Yanan, HU Kaikai, CHEN Gang, SHU Hui, LI Ziyuan

“…Data samples are amplified by time-long segmentation, and time domain and frequency domain features of a specific frequency doubling section are extracted as the input of machine learning. …”
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