Results 1 to 10 of about 23,619,888 (317)
Quantum intrusion detection system using outlier analysis [PDF]
Scientific ReportsIn the field of cybersecurity, hackers often enter computer systems despite current security measures, owing to the huge amount of network traffic that makes intruder identification difficult.
Tae Hoon Kim, S. Madhavi
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A Guide for Private Outlier Analysis. [PDF]
IEEE Lett Comput Soc, 2020 The increasing societal demand for data privacy has led researchers to develop methods to preserve privacy in data analysis. However, outlier analysis, a fundamental data analytics task with critical applications in medicine, finance, and national security, has only been analyzed for a few specialized cases of data privacy.
Asif H, Papakonstantinou PA, Vaidya J.
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Outlier analysis: Natural resources and immigration policy. [PDF]
PLoS ONE, 2022 This replication underlines the importance of outlier diagnostics since many researchers have long neglected influential observations in OLS regression analysis.
Seung-Whan Choi
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TDS Similarity: Outlier Analysis Using a Similarity Index to Compare Time-Series Responses of Temporal Dominance of Sensations Tasks. [PDF]
Foods, 2023 Temporal dominance of sensations (TDS) methods are used to record temporally developing sensations while eating food samples. Results of TDS tasks are typically discussed using averages across multiple trials and panels, and few methods have been ...
Natsume H, Okamoto S, Nagano H.
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TM4SF4 and LRRK2 Are Potential Therapeutic Targets in Lung and Breast Cancers through Outlier Analysis. [PDF]
Cancer Res Treat, 2021 Purpose To find biomarkers for disease, there have been constant attempts to investigate the genes that differ from those in the disease groups. However, the values that lie outside the overall pattern of a distribution, the outliers, are frequently ...
Jung K +15 more
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International Journal of Computer Applications, 2021 The main focus of this research is temporal data. Temporal data means data depends on time. A large number of applications generate a set of temporal data.
Pankaj Kumar Manjhi +2 more
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Outlier analysis for accelerating clinical discovery: An augmented intelligence framework and a systematic review. [PDF]
PLOS Digit HealthClinical discoveries largely depend on dedicated clinicians and scientists to identify and pursue unique and unusual clinical encounters with patients and communicate these through case reports and case series.
Janoudi G +7 more
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Unsupervised Outlier Profile Analysis [PDF]
Cancer Informatics, 2014 In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof.
Debashis Ghosh, Song Li
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Outlier analysis for microarray gene
International journal of health sciences, 2022 Pre-processing data is a critical component of data mining, as it comprises anomaly identification, outlier analysis, and dimensionality reduction utilising a distance-based technique. This research study demonstrates that in order to cope with scarcity difficulties in high dimensional spaces, computations should be limited to such data.
M Rashmi, Manish Varshney
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Robust principal component analysis for accurate outlier sample detection in RNA-Seq data
BMC Bioinformatics, 2020 Background High throughput RNA sequencing is a powerful approach to study gene expression. Due to the complex multiple-steps protocols in data acquisition, extreme deviation of a sample from samples of the same treatment group may occur due to technical ...
Xiaoying Chen +4 more
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