Results 61 to 70 of about 2,525,472 (291)

GrImp: Granular Imputation of Missing Data for Interpretable Fuzzy Models

Axioms
Data incompleteness is a common problem in real-life datasets. This is caused by acquisition problems, sensor failures, human errors, and so on. Missing values and their subsequent imputation can significantly affect the performance of data-driven models
Krzysztof Siminski, Konrad Wnuk
doaj   +1 more source

Finding Top- $k$ Dominance on Incomplete Big Data Using MapReduce Framework

IEEE Access, 2018
Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It is very difficult to retrieve information from this type of dataset when it becomes large.
Payam Ezatpoor, Justin Zhan, Jimmy Ming-Tai Wu, Carter Chiu   +3 more
doaj   +1 more source

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source

Multivariate Tests with Incomplete Data

The Annals of Statistics, 1983
In the context of a normal model, testing problems with missing data are considered. Tests on means are treated when independent extra data on the first $p_1$ variates of $p$ variates is available in addition to complete data. For testing that the mean of the first $p_1$ variates is zero, the LRT is UMP invariant, but for testing that the whole mean is
Eaton, Morris, Kariya, Takeaki
openaire   +2 more sources

In situ molecular organization and heterogeneity of the Legionella Dot/Icm T4SS

FEBS Letters, EarlyView.
We present a nearly complete in situ model of the Legionella Dot/Icm type IV secretion system, revealing its central secretion channel and identifying new components. Using cryo‐electron tomography with AI‐based modeling, our work highlights the structure, variability, and mechanism of this complex nanomachine, advancing understanding of bacterial ...
Przemysław Dutka, Yuxi Liu, Stefano Maggi, Debnath Ghosal, Jue Wang, Prashant P. Damke, Stephen D. Carter, Wei Zhao, Sukhithasri Vijayrajratnam, Joseph P. Vogel, Carrie L. Shaffer, Grant J. Jensen   +11 more
wiley   +1 more source

A Deep Similarity Metric Method Based on Incomplete Data for Traffic Anomaly Detection in IoT

Applied Sciences, 2019
In recent years, with the development of the Internet of Things (IoT) technology, a large amount of data can be captured from sensors for real-time analysis.
Xu Kang, Bin Song, Fengyao Sun
doaj   +1 more source

Methods to Handle Incomplete Data

MAMC Journal of Medical Sciences, 2020
Context: The major question for data analysis is determining the appropriate analytic approach in the presence of incomplete observations. The most common solution to handle missing data in a data set is imputation, where missing values are estimated and
Vinny Johny, Mariamma Philip, Swathi Augustine   +2 more
doaj   +1 more source

Distribution of Mutual Information from Complete and Incomplete Data

, 2004
Mutual information is widely used, in a descriptive way, to measure the stochastic dependence of categorical random variables. In order to address questions such as the reliability of the descriptive value, one must consider sample-to-population ...
Hutter, Marcus, Zaffalon, Marco
core   +2 more sources

Regression SVM for Incomplete Data

Schedae Informaticae, 2017
The use of machine learning methods in the case of incomplete data is an important task in many scientific fields, like medicine, biology, or face recognition. Typically, missing values are substituted with artificial values that are estimated from the known samples, and the classical machine learning algorithms are applied.
Struski, Łukasz, Śmieja, Marek, Zieliński, Bartosz, Tabor, Jacek   +3 more
openaire   +3 more sources

The (Glg)ABCs of cyanobacteria: modelling of glycogen synthesis and functional divergence of glycogen synthases in Synechocystis sp. PCC 6803

FEBS Letters, EarlyView.
We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee, Dimitrios Bekiari, Sofia Doello, Karl Forchhammer   +3 more
wiley   +1 more source