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Clusters distance
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The electronic states of FeSin −/0/+ (n = 1-2) clusters have been investigated with DFT, CASPT2, and DMRGCASPT2 methods. By using relatively large active spaces, the DMRG-CASPT2 method is found to provide highly accurate relative energies for the various relevant electronic states. Leading configurations, bond distances, harmonic vibrational frequencies, and relative energies for the low-lying states of the title clusters are reported.
9p
dianmotminh02
03-05-2024
4
2
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Ebook "Data mining - A heuristic approach" includes content: From evolution to immune to swarm to a simple introduction to modern heuristics; approximating proximity for fast and robust distance based clustering; on the use of evolutionary algorithms in data mining, the discovery of interesting nuggets using heuristic techniques, estimation of distribution algorithms for feature subset selection in large dimensionality domains,... and other contents.
310p
haojiubujain09
21-11-2023
3
3
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Colorectal cancer (CRC) is among the most frequently diagnosed cancers. Approximately 20–30% of stage I-III CRC patients develop a recurrent tumour or metastases after curative surgical resection. Post-operative follow-up is indicated for the first five years after curative surgical resection.
11p
vioracle
29-09-2023
4
2
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Information retrieval techniques: Lecture 41. The main topics covered in this chapter include: what is clustering; improving search recall; issues for clustering; notion of similarity/distance; hard vs. soft clustering; clustering algorithms;... Please refer to the content of document.
30p
tieuvulinhhoa
22-09-2022
9
4
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Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated.
14p
viaristotle
29-01-2022
7
0
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The Jaccard index was used to determine the new method’s accuracy performance. The results showed a significant improvement in the clustering of the developed algorithm than the standard K-PowerMeans. The results showed a significant improvement in the clustering of the developed algorithm than the standard K-PowerMeans.
23p
spiritedaway36
28-11-2021
25
5
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The rapid development of Next-Generation Sequencing technologies enables sequencing genomes with low cost. The dramatically increasing amount of sequencing data raised crucial needs for efficient compression algorithms.
9p
vijeeni2711
24-07-2021
15
0
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The present investigation was undertaken with 30 rice genotypes to estimate the nature and magnitude of genetic divergence for yield and nutritional traits. The 30 genotypes were categorized into six clusters based on D² values using agglomerative hierarchical clustering complete linkage based on Mahalanobis distance. Cluster I was largest comprising of nine genotypes followed by cluster III and IV comprising of seven and six genotypes respectively.
13p
chauchaungayxua11
23-03-2021
14
2
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The present study aims at studying the genetic variability using parameters like GCV, PCV, heritability, genetic advance and identifying parents with high genetic divergence to use them in future hybridization programmes.
8p
chauchaungayxua10
18-03-2021
17
2
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Genetic diversity among sixty three okra genotypes was estimated using Mahalanobis D2 statistic. The genotypes were grouped into nine clusters. The maximum number of genotypes was found in cluster I (36) followed by cluster III (15) and Cluster II (6). Remaining all were solitary clusters with single genotype.
6p
gaocaolon9
22-12-2020
17
2
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A set of 48 rice genotypes were subjected to Mahalanobis D2 analysis to assess the genetic diversity. All these genotypes were grouped into seven clusters with maximum inter cluster distance between cluster IV and cluster VII (55.28) and minimum inter cluster distance between cluster II and cluster IV (16.14).
5p
gaocaolon9
22-12-2020
12
2
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In order to find out the selection criteria thirty three genotypes were evaluated during kharif 2019-20 which includes 20 hybrids, 12 parents and a check (ICH-66). Data was subjected to principal component analysis (PCA) to reduce the number of variables in the original data set to a more significant set of variables, while maintaining maximum information.
10p
trinhthamhodang1216
19-11-2020
12
1
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Sixty genotypes of roselle (Hibiscus sabdariffa L.) were evaluated in North Coastal zone of Andhra Pradesh at Agricultural Research Station, Ragolu for fiber yield and eleven contributing characters during Kharif, 2013 & 2014 and grouped them into six clusters based on D2 analysis.
7p
caygaocaolon8
07-11-2020
12
1
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In genomics, hierarchical clustering (HC) is a popular method for grouping similar samples based on a distance measure. HC algorithms do not actually create clusters, but compute a hierarchical representation of the data set.
11p
vikentucky2711
26-11-2020
8
0
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Chemical or small interfering (si) RNA screens measure the effects of many independent experimental conditions, each applied to a population of cells (e.g., all of the cells in a well). High-content screens permit a readout (e.g., fluorescence, luminescence, cell morphology) from each cell in the population.
20p
vikentucky2711
24-11-2020
10
1
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Identification of biological specimens is a requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but generally do not scale to arbitrarily large genomes and arbitrarily large phylogenetic distances.
10p
vioklahoma2711
19-11-2020
6
2
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In the context of infectious disease, sequence clustering can be used to provide important insights into the dynamics of transmission. Cluster analysis is usually performed using a phylogenetic approach whereby clusters are assigned on the basis of sufficiently small genetic distances and high bootstrap support (or posterior probabilities).
9p
vioklahoma2711
19-11-2020
7
1
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In this study, Sentinel–1A satellite imagery is used to extract the coastline in Phan Thiet City. The boundary between land and water is determined by a two–step process: fuzzy clustering and interactive thresholding. Subsequently, the coastline in the study area was extracted into vector form. Finally, this shoreline is compared to manually digitized shoreline. There are 350 locations considered to determine the distance between two shorelines, of which 274 locations (77%) are 0 to 5 m (equivalent to ½ pixel) and 76 (23%) locations are over 5 m.
10p
cothumenhmong8
05-11-2020
26
1
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A novel pathway-based distance score enhances assessment of disease heterogeneity in gene expression
Distance based unsupervised clustering of gene expression data is commonly used to identify heterogeneity in biologic samples. However, high noise levels in gene expression data and relatively high correlation between genes are often encountered, so traditional distances such as Euclidean distance may not be effective at discriminating the biological differences between samples.
17p
viflorida2711
30-10-2020
11
2
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This study was carried out to assess the genetic divergence among 15 cluster bean genotypes using mahalanobis D2 . Fifteen genotypes were grouped into four clusters. Maximum (6) genotypes were included in cluster II and minimum (1) in clusters IV.
9p
nguathienthan8
20-10-2020
10
2
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