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Puti Yan, Zhen Cao, Jiangbo Peng, Chaobo Yang, Xin Yu, Penghua Qiu, Shanchun Zhang, Minghong Han, Wenbei Liu and Zuo Jiang
A flame?s structural feature is a crucial parameter required to comprehensively understand the interaction between turbulence and flames. The generation and evolution processes of the structure feature have rarely been investigated in lean blowout (LBO) ...
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Konstantinos P. Fourkiotis and Athanasios Tsadiras
In today?s evolving global world, the pharmaceutical sector faces an emerging challenge, which is the rapid surge of the global population and the consequent growth in drug production demands. Recognizing this, our study explores the urgent need to stren...
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Zhifei Xi, Yingxin Kou, You Li, Zhanwu Li and Yue Lv
Air combat situation assessment is the basis of target assignment and maneuver decisions. The current air combat situation assessment models, whether nonparametric or parametric, ignore the continuity and timing of situation changes, making the situation...
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Daiwei Zhang, Chunyang Ying, Lei Wu, Zhongqiu Meng, Xiaofei Wang and Youhua Ma
Timely and accurate extraction of crop planting structure information is of great importance for food security and sustainable agricultural development. However, long time series data with high spatial resolution have a much larger data volume, which ser...
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Daniel Ricardo Sandoval Serrano, Juan Carlos Rincón, Julián Mejía-Restrepo, Edward Rolando Núñez-Valdez and Vicente García-Díaz
Forecasting medical costs is crucial for planning, budgeting, and efficient decision making in the health industry. This paper introduces a proposal to forecast costs through techniques such as a standard model of long short-term memory (LSTM); and patie...
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Shlomo Dubnov
Capturing long-term statistics of signals and time series is important for modeling recurrent phenomena, especially when such recurrences are a-periodic and can be characterized by the approximate repetition of variable length motifs, such as patterns in...
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Iurii Katser, Viacheslav Kozitsin, Victor Lobachev and Ivan Maksimov
Offline changepoint detection (CPD) algorithms are used for signal segmentation in an optimal way. Generally, these algorithms are based on the assumption that signal?s changed statistical properties are known, and the appropriate models (metrics, cost f...
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Halima Saker, Rainer Machné, Jörg Fallmann, Douglas B. Murray, Ahmad M. Shahin and Peter F. Stadler
The problem of segmenting linearly ordered data is frequently encountered in time-series analysis, computational biology, and natural language processing. Segmentations obtained independently from replicate data sets or from the same data with different ...
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Ignazio Gallo, Riccardo La Grassa, Nicola Landro and Mirco Boschetti
In this paper, we provide an innovative contribution in the research domain dedicated to crop mapping by exploiting the of Sentinel-2 satellite images time series, with the specific aim to extract information on ?where and when? crops are grown. The fina...
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Yue Sun, Sandor Brockhauser and Péter Hegedus
In scientific research, spectroscopy and diffraction experimental techniques are widely used and produce huge amounts of spectral data. Learning patterns from spectra is critical during these experiments. This provides immediate feedback on the actual st...
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