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Updated: Jan 12, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

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人工智能增强的矿山尾矿集群使用地统数据增强和高斯混合模型

Nasser Madani1, Sergei Sabanov2

  • 1School of Mining and Geosciences, Nazarbayev University, Kabanbay Batyr 53, Astana, 010000, Kazakhstan. nasser.madani@nu.edu.kz.

Scientific reports
|November 6, 2025
PubMed
概括

再加工矿山尾矿为绿色技术提供了有价值的原材料. 使用地球统计学和高斯混合模型 (GMM) 的AI框架改进了域建模,以便从这些复杂的沉积物中有效地回收资源.

关键词:
集群集成是指集群集成.高斯混合模型 (GMM)地理统计数据增强矿山尾矿是矿山的尾矿.

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Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores10:31

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Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Shape and Texture of Coarse Aggregate01:25

Shape and Texture of Coarse Aggregate

Aggregate shape is classified based on the relative sharpness or roundness of the edges and corners. This classification includes categories like rounded, angular, elongated, and flaky, each with specific characteristics. Rounded aggregates, fully shaped by attrition, are typical of river or seashore gravel, while angular aggregates, such as crushed rock, have well-defined edges. Aggregates that are elongated and flaky are less desirable, as they can reduce the workability and strength of...
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Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
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