Estimation of inertia demand in power systems considering wind power virtual inertia by Hongchun SHU, Haifei DONG, Jing CHEN, Guangxue WANG, Xi WANG, Botao SHI

“…The proposed method evaluates the inertia requirements of a power system at a certain level of renewable energy penetration to ensure that the system’s operational frequency stays with the safety boundaries after a system disturbance instead of increasing the inertia level to 100% synchronous machines. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…Therefore, we propose a framework that begins with a robust segmentation method for extracting sound clips that potentially contain deer vocalizations. …”
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Automated high-temporal-resolution multi-element river water monitoring with ICP-MS by Mohamed Harhash, Jan G. Wiederhold, Ingrid Nett, Julia Arndt, Alexander Zavarsky, Thomas A. Ternes, Lars Duester

“…Thus, there is an urgent need for continuous fully quantitative high-temporal-resolution multi-element monitoring of river water to provide comprehensive datasets to improve water management, also with respect to machine learning training and prognosis. Results Therefore, we developed an automated atline method using inductively coupled plasma-mass spectrometry (ICP-MS) to continuously measure 56 elements in river water at a high time resolution of one mixed sample per hour. …”
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Research on the Macrocell Wireless Channel Model Based on Physic-Inspired Support Vector Regression Algorithm Wireless Channel Model in Macrocell Environment by Qi Yao, Zhongyu Liu, Lixin Guo, Jiang Guo, Zuoyong Nan, Wei Liu, Jiangting Li

“…The method embeds the building transmission model (BTM) into a machine learning framework based on support vector regression. …”
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Design optimization and precision requirements of an endcap ion trap for single-ion optical clock applications by Chaowei Wang, Shaoyang Dai, Yani Zuo, Fang Fang

“…Based on this, the study further explored the machining accuracy of certain dimensions, concluding that the required high machining accuracy values for the radio frequency electrodes and the endcap electrodes are ±3 and ±7 μm, respectively, while the aperture machining accuracy requirements are ±3 and ±22 μm, respectively. …”
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Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

“…Considering these multiple influencing factors, herein, a method is proposed to predict the milling stability and determine optimal machining parameters based on a bootstrap aggregating (bagging) procedure and the non-dominated sorting genetic algorithm–Ⅱ (NSGA–Ⅱ). …”
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Personalized approaches to the treatment of uterine leiomyoma by N. S. Oliinyk, N. S. Lutsenko

“…Ultrasound diagnostics was performed following methodic of the color Doppler imaging (CDI) with Voluson Е8 machine (UK) using vaginal transducer with the frequency of 7.5 MHz and convex abdominal transducer with the frequency of 3.5 MHz. …”
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An Extensible Schema For Building Large Weakly-labeled Semantic Corpora by S.Matthew English

“… In NLP data drives research, as evidenced by the frequency with which seminal works of database engineering such as The Penn Treebank have been employed as a basis for experimentation. …”
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Three-Axis Vibration Isolation of a Full-Scale Magnetorheological Seat Suspension by Young T. Choi, Norman M. Wereley, Gregory J. Hiemenz

“…This study examines the three-axis vibration isolation capabilities of a full-scale magnetorheological (MR) seat suspension system utilizing experimental methods to assess performance under both single-axis and simultaneous three-axis input conditions. …”
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Advanced bearing fault detection at varying rotational speeds using PSO-optimized SVM and CDET feature selection by Hongxu Chai, Xiaoshi Ma, Feng Zhu, Yandong Hu

“…The outcomes demonstrate that specific features can effectively differentiate various bearing conditions at different speeds, highlighting the efficacy of the recommended approach compared to other fault detection methods.…”
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Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes by Yanying Li, Zaiwen Ni, Binqing Xiao

“…The empirical results demonstrate that the E-Heuristic Miner significantly outperforms traditional machine learning methods and process mining algorithms in process anomaly detection. …”
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Comparison of the ability of Reciproc and Reciproc Blue instruments to reach the full working length with or without glide path preparation by Mehmet Adıguzel, Pelin Tufenkci

“…ObjectivesThe purpose of the present study was to compare the mean preparation times and frequency with which Reciproc and Reciproc Blue instruments reached the full working length in mandibular molars, with or without glide path preparation.Materials and MethodsPreviously untreated mesiobuccal and mesiolingual canals with completely formed apices were randomly divided into 6 groups (n = 50) depending on the usage of Reciproc (RC; VDW), Reciproc Blue (RC Blue; VDW), C-Pilot (CP; VDW), and R-Pilot (RP; VDW) files: RC, RC Blue, RC + C-Pilot (RC-CP), RC-Blue + C-Pilot (RC Blue-CP), RC+R-Pilot (RC-RP), and RC Blue + R-Pilot (RC Blue-RP). …”
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Vibration cancellation controller design of magnetic levitation stage for fast and precise positioning by Takanori KATO, Motohiro TAKAHASHI

“…In the proposed method, the conditions for cancelling vibration modes are derived and shown in the frequency domain. …”
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Geomagnetic Field Based Indoor Landmark Classification Using Deep Learning by Bimal Bhattarai, Rohan Kumar Yadav, Hui-Seon Gang, Jae-Young Pyun

“…The experimental results show that our proposed models outperform other traditional positioning approaches with machine learning methods, such as support vector machine and k-nearest neighbors.…”
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Predicting the hospitalization burdens of patients with mental disease: a multiple model comparison by Lu Hou, Lu Hou, Jing Zhang, Jing Zhang, Li Li, Yelin Weng, Ziyu Yang, Zhiguo Liu

“…The findings support tailored resource allocation and early intervention for high-risk groups.ConclusionThis study showcased the effectiveness of machine learning methods in predicting the hospitalization burden of inpatients with mental disorders, thereby offering scientific decision support for medical institutions. …”
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Joint Intensity and Spatio-Temporal Representation Learning for Extreme Precipitation Nowcasting by Zefeng Pan, Renlong Hang, Qingshan Liu, Chunxiang Shi, Zhiqiang Xu, Xiao-Tong Yuan

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Exploring Spatio-Temporal Dynamics of Future Extreme Precipitation, Runoff, and Flood Risk in the Hanjiang River Basin, China by Dong Wang, Weiwei Shao, Jiahong Liu, Hui Su, Ga Zhang, Xiaoran Fu

“…In this framework, a GCMs statistical downscaling method based on machine learning is used to project future precipitation, the PLUS model is used to project future land use, the digitwining watershed model (DWM) is used to project future runoff, and the entropy weight method is used to calculate risk. …”
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Digital technology for spectral analysis of oscillation parameters by A. V. Gulaj, V. M. Zajcev

“…Performing the Fourier analysis of the harmonic composition of oscillations is an effective approach to the study of vibration processes in machines and mechanisms. This method of express control remains relevant and highly demanded in the acoustic diagnostics of machines due to its relatively high informativeness. …”
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Effects of Heating and Liquid Nitrogen on Mechanical Characteristics and Rockburst Characteristics of Granite by Xue Li, Yi Xue, Fa-ning Dang, Zhihao Zhang, Lin Zhu, Shanjie Su, Shengcheng Wang, Ruifu Liu

“…With the cycle times of LN2 actions increasing, the AE ring count of granite and the frequency and amplitude of energy in each stage have an upward trend. …”
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Application of Fourth Industrial Revolution technologies to enhance supply chain sourcing: A systematic literature review by Refentse L. Selepe, Olasumbo A. Makinde, Thomas Munyai

“…Simulation, Internet of things (IoT), machine learning (ML), additive manufacturing and radio frequency identification (RFID) were found to be critical technologies. …”
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