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Published in 2022 at "Biotechnology and Bioengineering"
DOI: 10.1002/bit.28211
Abstract: Microbial consortia constitute a promising tool for achieving high‐value chemical bio‐production. However, customizing the consortium ratio remains challenging. Herein, an asymmetry distribution‐based synthetic consortium (ADSC) was developed to switch cell phenotypes using shikimate synthesis for…
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Keywords:
distribution based;
production;
asymmetry distribution;
distribution ... See more keywords
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Published in 2019 at "Journal of Statistical Theory and Practice"
DOI: 10.1007/s42519-019-0066-3
Abstract: AbstractIn this paper, we discussed the estimation of the unknown parameters in addition to survival and hazard functions for a three-parameter Burr-XII distribution based on unified hybrid censored data. The maximum likelihood and Bayes method…
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Keywords:
three parameter;
distribution based;
mcmc;
parameter burr ... See more keywords
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Published in 2022 at "Analytical chemistry"
DOI: 10.1021/acs.analchem.2c02991
Abstract: Herein, we present the use of mass distribution-based isotopic shifts in high-resolution cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS)-based separations to characterize various isomeric species as well as conformers. Specifically, by using the observed relative arrival…
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Keywords:
mass distribution;
high resolution;
distribution based;
methodology ... See more keywords
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Published in 2017 at "Scientific Reports"
DOI: 10.1038/srep46201
Abstract: Scientific Reports 6: Article number: 28767; published online: 30 June 2016; updated: 25 April 2017 In the Article, we did not take into account the entanglement swapping that can be caused by eavesdropping efforts. Due…
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Keywords:
corrigendum one;
step quantum;
distribution based;
key distribution ... See more keywords
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Published in 2018 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2017.1398256
Abstract: ABSTRACT Ranked set sampling (RSS) is an efficient method for estimating parameters when exact measurement of observation is difficult and/or expensive. In this paper, we provide maximum likelihood estimation of the shape and scale parameters…
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Keywords:
rayleigh distribution;
estimation;
distribution based;
generalized rayleigh ... See more keywords
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Published in 2018 at "American Journal of Mathematical and Management Sciences"
DOI: 10.1080/01966324.2017.1396943
Abstract: SYNOPTIC ABSTRACT We consider estimation of unknown parameters of a two-parameter Kumaraswamy distribution with hybrid censored samples. We obtain maximum likelihood estimates using an expectation-maximization algorithm. Bayes estimates are derived under the squared error loss…
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Keywords:
kumaraswamy distribution;
estimation;
parameter estimation;
distribution based ... See more keywords
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2
Published in 2023 at "Journal of orthopaedic trauma"
DOI: 10.1097/bot.0000000000002600
Abstract: OBJECTIVE Calculate the minimal clinically important differences (MCID) of Patient Reported Outcome Information System Physical Function (PROMIS PF) scores for patients with operatively treated tibial shaft fractures. DESIGN Retrospective Cohort Study. SETTING A Level 1…
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Keywords:
anchor based;
tibial shaft;
distribution based;
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1
Published in 2022 at "Clinical Orthopaedics and Related Research"
DOI: 10.1097/corr.0000000000002434
Abstract: Abstract Background The minimum clinically important difference (MCID) is intended to detect a change in a patient-reported outcome measure (PROM) large enough for a patient to appreciate. Their growing use in orthopaedic research stems from…
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Keywords:
mcid;
mcid values;
distribution based;
anchor based ... See more keywords
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Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3262313
Abstract: Block ciphers are widely used for securing data and are known for their resistance to various types of attacks. The strength of a block cipher against these attacks often depends on the S-boxes used in…
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Keywords:
nonlinearity;
distribution based;
gaussian distribution;
distribution ... See more keywords
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Published in 2022 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2020.2985965
Abstract: The imbalanced data classification problem widely exists in many real-world applications. Data resampling is a promising technique to deal with imbalanced data through either oversampling or undersampling. However, the traditional data resampling approaches simply take…
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Keywords:
imbalanced data;
distribution based;
gaussian distribution;
data classification ... See more keywords
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Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2022.3161537
Abstract: Undersampling is one of the most popular techniques for dealing with class-imbalance problems. Various undersampling methods have emerged over the past few decades. Each of them exhibits the superiority in some scenarios. However, selecting representative…
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Keywords:
spatial distribution;
sdus;
class;
imbalanced undersampling ... See more keywords