scholarly journals Phylogenetic relations and mitogenome‐wide similarity metrics reveal monophyly of Penaeus sensu lato

2021 ◽  
Vol 11 (5) ◽  
pp. 2040-2049
Author(s):  
Vinaya Kumar Katneni ◽  
Mudagandur S. Shekhar ◽  
Ashok Kumar Jangam ◽  
Balasubramanian C. Paran ◽  
Ashok Selvaraj ◽  
...  
Keyword(s):  
Similarity Metrics ◽  
Phylogenetic Relations

USE OF SIMILARITY METRICS IN TEMPLATE-BASED DETECTION OF OBJECTS IN IMAGES

2019 ◽  
Vol 78 (14) ◽  
pp. 1249-1261
Author(s):  
O. Rubel ◽  
S. K. Abramov ◽  
V. V. Abramova ◽  
V. V. Lukin
Keyword(s):  
Similarity Metrics ◽  
Detection Of Objects

Methods for detecting and correcting contextual data quality problems

2021 ◽  
Vol 25 (4) ◽  
pp. 763-787
Author(s):  
Alladoumbaye Ngueilbaye ◽  
Hongzhi Wang ◽  
Daouda Ahmat Mahamat ◽  
Ibrahim A. Elgendy ◽  
Sahalu B. Junaidu
Keyword(s):  
Data Quality ◽  
Quality Evaluation ◽  
Web Applications ◽  
Support Vector ◽  
Similarity Metrics ◽  
Distributed Data ◽  
Contextual Data ◽  
Formal Taxonomy ◽  
E Learning ◽  
High Scalability

Knowledge extraction, data mining, e-learning or web applications platforms use heterogeneous and distributed data. The proliferation of these multifaceted platforms faces many challenges such as high scalability, the coexistence of complex similarity metrics, and the requirement of data quality evaluation. In this study, an extended complete formal taxonomy and some algorithms that utilize in achieving the detection and correction of contextual data quality anomalies were developed and implemented on structured data. Our methods were effective in detecting and correcting more data anomalies than existing taxonomy techniques, and also highlighted the demerit of Support Vector Machine (SVM). These proposed techniques, therefore, will be of relevance in detection and correction of errors in large contextual data (Big data).

scholarly journals The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances

2021 ◽  
Author(s):  
Anne Driemel ◽  
André Nusser ◽  
Jeff M. Phillips ◽  
Ioannis Psarros
Keyword(s):  
Density Estimation ◽  
Lower Bounds ◽  
Upper And Lower Bounds ◽  
Similarity Metrics ◽  
Vc Dimension ◽  
Set Systems ◽  
Polygonal Curves ◽  
The Individual ◽  
Curve Similarity ◽  
Metric Balls

AbstractThe Vapnik–Chervonenkis dimension provides a notion of complexity for systems of sets. If the VC dimension is small, then knowing this can drastically simplify fundamental computational tasks such as classification, range counting, and density estimation through the use of sampling bounds. We analyze set systems where the ground set X is a set of polygonal curves in $$\mathbb {R}^d$$ R d and the sets $$\mathcal {R}$$ R are metric balls defined by curve similarity metrics, such as the Fréchet distance and the Hausdorff distance, as well as their discrete counterparts. We derive upper and lower bounds on the VC dimension that imply useful sampling bounds in the setting that the number of curves is large, but the complexity of the individual curves is small. Our upper and lower bounds are either near-quadratic or near-linear in the complexity of the curves that define the ranges and they are logarithmic in the complexity of the curves that define the ground set.

Use of tall fescue EST-SSR markers in phylogenetic analysis of cool-season forage grasses

Genome ◽  
2005 ◽  
Vol 48 (4) ◽  
pp. 637-647 ◽  
Author(s):  
M A. Rouf Mian ◽  
Malay C Saha ◽  
Andrew A Hopkins ◽  
Zeng-Yu Wang
Keyword(s):  
Phylogenetic Analysis ◽  
Ssr Markers ◽  
Tall Fescue ◽  
Related Species ◽  
Grass Species ◽  
Forage Grass ◽  
Forage Grasses ◽  
Cool Season ◽  
Phylogenetic Relations ◽  
Wide Range

Microsatellites or simple sequence repeats (SSRs) are highly useful molecular markers for plant improvement. Expressed sequence tag (EST)-SSR markers have a higher rate of transferability across species than genomic SSR markers and are thus well suited for application in cross-species phylogenetic studies. Our objectives were to examine the amplification of tall fescue EST-SSR markers in 12 grass species representing 8 genera of 4 tribes from 2 subfamilies of Poaceae and the applicability of these markers for phylogenetic analysis of grass species. About 43% of the 145 EST-SSR primer pairs produced PCR bands in all 12 grass species and had high levels of polymorphism in all forage grasses studied. Thus, these markers will be useful in a variety of forage grass species, including the ones tested in this study. SSR marker data were useful in grouping genotypes within each species. Lolium temulentum, a potential model species for cool-season forage grasses, showed a close relation with the major Festuca–Lolium species in the study. Tall wheatgrass was found to be closely related to hexaploid wheat, thereby confirming the known taxonomic relations between these species. While clustering of closely related species was found, the effectiveness of such data in evaluating distantly related species needs further investigations. The phylogenetic trees based on DNA sequences of selected SSR bands were in agreement with the phylogenetic relations based on length polymorphism of SSRs markers. Tall fescue EST-SSR markers depicted phylogenetic relations among a wide range of cool-season forage grass species and thus are an important resource for researchers working with such grass species.Key words: phylogeny, EST-SSR, forage grasses, tall fescue.

Morphological and Phylogenetic Relations Among the Darwin's Finches

Evolution ◽  
1984 ◽  
Vol 38 (5) ◽  
pp. 921 ◽  
Author(s):  
Dolph Schluter
Keyword(s):  
Darwin's Finches ◽  
Phylogenetic Relations ◽  
Darwin’S Finches

Phylogenetic relations of European shrubby taxa of the genusUsnea

2011 ◽  
Vol 43 (5) ◽  
pp. 427-444 ◽  
Author(s):  
Lauri SAAG ◽  
Tiiu TÕRRA ◽  
Andres SAAG ◽  
Ruth DEL-PRADO ◽  
Tiina RANDLANE
Keyword(s):  
Maximum Parsimony ◽  
Chemical Separation ◽  
Molecular Data ◽  
Beta Tubulin ◽  
Phylogenetic Relations ◽  
Branch Lengths ◽  
Nuclear Its ◽  
Molecular Characters

AbstractThis study focuses on EuropeanUsneaspecies with sorediate shrubby thalli, with the aim to evaluate the morphological and chemical separation of species in the light of molecular data. Twenty-twoUsneaspecies, including widely distributed taxa such asU. diplotypus, U. fulvoreagens, U. glabrescens, U. lapponica, U. subfloridana, U. substerilisandU. wasmuthii, were included in the study using Bayesian and maximum parsimony analyses of nuclear ITS and beta-tubulin sequences. The analyses showed that: 1) most taxa that are morphologically well delimited are also distinct by means of molecular characters, 2) shrubby taxa in the sectionUsneathat are difficult to determine by traditional characters form a group of closely related but still genetically distinct entities, exceptU. diplotypusandU. substeriliswhich appear to be polyphyletic. The branch lengths differed largely between two parts of the ITS tree (sectionsUsneaandCeratinae).Usnea intermediais proposed as the sexually reproducing counterpart for the sorediateU. lapponica. Additionally, some new chemotypes ofUsneaspecies were determined.

scholarly journals A new subjective procedure for evaluation and development of texture similarity metrics

2011 ◽  
Author(s):  
Jana Zujovic ◽  
Thrasyvoulos N. Pappas ◽  
David L. Neuhoff ◽  
Rene van Egmond ◽  
Huib de Ridder
Keyword(s):  
Similarity Metrics

MuSim: Mutation-based Fault Localization Using Test Case Proximity

2021 ◽  
Vol 31 (05) ◽  
pp. 725-744
Author(s):  
Arpita Dutta ◽  
Amit Jha ◽  
Rajib Mall
Keyword(s):  
Fault Localization ◽  
Test Case ◽  
Test Cases ◽  
Similarity Metrics ◽  
Localization Technique ◽  
Evaluation Metric

Fault localization techniques aim to localize faulty statements using the information gathered from both passed and failed test cases. We present a mutation-based fault localization technique called MuSim. MuSim identifies the faulty statement based on its computed proximity to different mutants. We study the performance of MuSim by using four different similarity metrics. To satisfactorily measure the effectiveness of our proposed approach, we present a new evaluation metric called Mut_Score. Based on this metric, on an average, MuSim is 33.21% more effective than existing fault localization techniques such as DStar, Tarantula, Crosstab, Ochiai.

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