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Research article

First published 2026

A software reliability model with Weibull distributed fault removal efficiency for open source big data systems

Jinyong Wang, Pengda Li, Boxuan Li

Proceedings of the Institution of Mechanical Engineers,Part O: Journal of Risk and Reliability

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Research article

First published 2019-8

An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

Sinead J. Barton, Bryan M. Hennelly

Applied Spectroscopy

Open access

Research article

First published 2024-4

Quantifying Careless Responses in Student Evaluation of Teaching and Justifying Removal for Data Validity

Yingchen Wang

Sage Open

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Research article

First published 2010-11

EDAR: An Efficient Error Detection and Removal Algorithm for Next Generation Sequencing Data

Xiaohong Zhao, Lance E. Palmer, Randall Bolanos [...]

Journal of Computational Biology

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Research article

First published 2010-1

Personal Digital Assistants to Collect Data on Animal Carcass Removal from Roadways

Bridget M. Donaldson, Nelson W. Lafon

Transportation Research Record: Journal of the Transportation Research Board

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Research article

First published 2016-9

Reduce or remove: Individual sensor reliability profiling and data cleaning

Yihong Zhang, Claudia Szabo, Quan Z. Sheng

Intelligent Data Analysis: An International Journal

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Research article

First published 2020-10

MultiBaC: A strategy to remove batch effects between different omic data types

Manuel Ugidos, Sonia Tarazona, José M Prats-Montalbán [...]

Statistical Methods in Medical Research

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Research article

First published 2007-9

A Practical Algorithm to Remove Cosmic Spikes in Raman Imaging Data for Pharmaceutical Applications

Lin Zhang, Mark J. Henson

Applied Spectroscopy

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Research article

First published 2022-8

Investigating the Safety Effectiveness of Wildlife–Vehicle Crash Countermeasures using a Bayesian Approach with a Comparison between Carcass Removal Data and Traditional Crash Data

Irfan U. Ahmed, Mohamed M. Ahmed

Transportation Research Record: Journal of the Transportation Research Board

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Research article

First published 2018-5

Smooth Factor Analysis (SFA) to Effectively Remove High Levels of Noise from Spectral Data Sets

Yeonju Park, Isao Noda, Young Mee Jung

Applied Spectroscopy

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