Understanding the Origin of SSR in Series-Compensated DFIG-Based Wind Farms: Analysis Techniques and Tuning by Roberto Moreno-Sanchez, C. Alberto Nunez-Gutierrez, Nancy Visairo-Cruz, Julio Hernandez-Ramirez, Juan Segundo-Ramirez

“…This paper is dedicated to presenting control-tuning methodologies for the rotor-side converter (RSC) and grid-side converter (GSC) of series-compensated DFIG-based wind farms (WF) and to determining the origin of subsynchronous resonance (SSR). …”
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Origin and originality of John Calvin's 'Harmony of the Law', the expository project on Exodus-Deuteronomy (1559-1563) by E. A. de Boer

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The application of Vavilov’s approaches to the phylogeny and evolution of cultivated species of the genus <i>Avena</i> L. by I. G. Loskutov, A. A. Gnutikov, E. V. Blinova, A. V. Rodionov

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Use of Flavonoids and Cinnamates, the Main Photoprotectors with Natural Origin by Alesandra R. Nunes, Ícaro G. P. Vieira, Dinalva B. Queiroz, Antonio Linkoln Alves Borges Leal, Selene Maia Morais, Débora Feitosa Muniz, João Tavares Calixto-Junior, Henrique Douglas Melo Coutinho

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ON CALCULATING SUMS OF SOME DOUBLE SERIES by V. I. Kuzovatov, A. S. Bushkova

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The Origin of Synergetic Effect in Mixed Mn-Co Oxide with Spinel Structure for Catalytic Oxidation of CO by Olga A. Bulavchenko, Vladimir A. Rogov, Evgeny Yu. Gerasimov, Egor E. Aydakov, Anna M. Kremneva

“…In this work, the origin of the synergetic effect in mixed Mn_xCo_3-xO₄ oxides with the spinel structure in the CO oxidation reaction was tested. …”
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Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation by Zhan Wang, Mwamba Kasongo Dahouda, Hyoseong Hwang, Inwhee Joe

“…The approach is based on the encoder in the long-short-term memory (LSTM) network, where input time-series data is converted into a lower-dimensional, implicit representation, and an attempt is made to reconstruct the original input data via a decoder. …”
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Noisy Approach to Intrinsically Mixed-State Topological Order by Ramanjit Sohal, Abhinav Prem

“…Specifically, we show that decoherence, previously interpreted as anyon condensation in a doubled Hilbert space, is more naturally phrased as, and provides a physical mechanism for, “gauging out” anyons in the original Hilbert space. We find that gauging out anyons generically results in imTO, with the decohered mixed state strongly symmetric under certain anomalous 1-form symmetries. …”
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Efficient Hamiltonian encoding algorithms for extracting quantum control mechanism as interfering pathway amplitudes in the Dyson series by Erez Abrams, Michael Kasprzak, Gaurav Bhole, Tak-San Ho, Herschel Rabitz

“…The amplitudes of pathway classes are computed by modulating the Hamiltonian matrix elements and decoding the subsequent evolution of the system rather than by direct computation of the individual terms in the Dyson series. The original implementation of Hamiltonian encoding was computationally intensive and became prohibitively expensive in large quantum systems. …”
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Time-Series Load Online Prediction of Wind Turbine Based on Adaptive Multisource Operational Data Fusion by Ruojin Wang, Xiaodong Wang, Deyi Fu, Bin Yang, Yingming Liu

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IAR 2.0: An Algorithm for Refining Inconsistent Annotations for Time-Series Data Using Discriminative Classifiers by Einari Vaaras, Manu Airaksinen, Okko Rasanen

“…As a result, we show that the labels produced by IAR 2.0 systematically improve classifier performance compared to using the original labels or a previous state-of-the-art method for label refinement. …”
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Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints by Mei Wang, Xinyuan Zhu, Guangyue Zhou, Kewen Li, Qingshan Wu, Wankai Fan

“…The Decoder is responsible for reconstructing the latent representations generated by the Encoder back into the original time series data. By utilizing LSTMA-AE, we aim to improve the accuracy of anomaly detection, while simultaneously employing mechanistic constraints to mitigate false alarm rates. …”
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Enhanced Adaptive Neural-Fuzzy Inference System for Dynamic Time Series Prediction Using Self-Feedback and Hybrid Training by Andrew Topper, Honglei Yao

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Hybrid GNSS time-series prediction method based on ensemble empirical mode decomposition with long short-term memory by Yu Zhou, Xiaoxing He, Shengdao Wang, Shunqiang Hu, Xiwen Sun, Jiahui Huang

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Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling by Patricia Virginia de Santana Lima, David Venâncio da Cruz, Albaro Ramon Paiva Sanz

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RESEARCH ON ISOMAP AND DEEP BELIEF NETWORK-BASED MACHINE HEALTH STATE ASSESSMENT by CHEN JianYe, WANG ShaJing, WEI CunHai, WEI ZhiJiang, WU Lin

“…The run-to-failure experiment of gearbox was conducted for validation studies, through a series of comparison experiments with the original features without space transformation, PCA and LE, HMM and BPNN, the proposed method in this paper is proved more effective for gear fault diagnosis and state assessment.…”
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Robust Output Feedback Disturbance Rejection Control by Simultaneously Estimating State and Disturbance by Jeang-Lin Chang

“…Through a series of transformations, we can transform the original system into two subsystems and then propose a sliding mode observer and a descriptor system form observer, respectively. …”
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University as a City and University as a State: Methodological Tools of William Clark by V. K. Pichugina, Z. A. Lurie

“…William Clark’s methodological tools applied to the study of the history and philosophy of higher education are presented in a series of articles 1996-2003 and especially in his book “Academic Charisma and the Origins of the Research University” (2006). …”
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Toward Enhanced Prediction of High‐Impact Solar Energetic Particle Events Using Multimodal Time Series Data Fusion Models by Pouya Hosseinzadeh, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi

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ABOUT THE MORPHOLOGY OF BUD SCALES AND CATAPHYLLS OF ULMUS GLABRA HUDS. (ULMACEAE) by I. S. Antonova, A. S. Popova

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