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tracking algorithm » tracking algorithms (Expand Search), training algorithms (Expand Search), making algorithm (Expand Search)
spatial tracking » optical tracking (Expand Search), spatial thinking (Expand Search), particle tracking (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
tracking algorithm » tracking algorithms (Expand Search), training algorithms (Expand Search), making algorithm (Expand Search)
spatial tracking » optical tracking (Expand Search), spatial thinking (Expand Search), particle tracking (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
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Image 4_Age- and sex-specific reference intervals for trace elements in infants and children: a multi-center study in Lincang, China.jpg
Published 2025“…</p>Methods<p>The data were obtained from the trace element test results of 3933 outpatients aged <18 years at three health examination centers in Lincang City between June 2014 and May 2024. …”
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Table 1_Age- and sex-specific reference intervals for trace elements in infants and children: a multi-center study in Lincang, China.docx
Published 2025“…</p>Methods<p>The data were obtained from the trace element test results of 3933 outpatients aged <18 years at three health examination centers in Lincang City between June 2014 and May 2024. …”
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Image 6_Age- and sex-specific reference intervals for trace elements in infants and children: a multi-center study in Lincang, China.jpg
Published 2025“…</p>Methods<p>The data were obtained from the trace element test results of 3933 outpatients aged <18 years at three health examination centers in Lincang City between June 2014 and May 2024. …”
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84
Model-Based Clustering of Categorical Data Based on the Hamming Distance
Published 2024“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to model the data. …”
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Flowchart of the proposed GSS algorithm.
Published 2024“…The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. …”
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Ricker seismic profile.
Published 2025“…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
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94
Noise reduction on testing sets from STEAD.
Published 2025“…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
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SNR comparison of real-field seismic profile.
Published 2025“…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
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96
The 147th single trace.
Published 2025“…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
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