Results 41 to 50 of about 84,843 (251)
Temporal and spatial outlier detection in wireless sensor networks
ETRI Journal, 2019 Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed ...
Hoc Thai Nguyen, Nguyen Huu Thai
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Outlier Detection in Classification Analysis: An Overview [PDF]
The Egyptian Statistical Journal, 1993 Some of the techniques used for detecting multivariate outliers can be used for detecting outliers in classification analysis. However, detecting outliers in classification analysis is more complicated than in any other analysis since the impact of an ...
Ramses Sadek
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Molecular Oncology, EarlyView.Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park +6 more
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Molecular Oncology, EarlyView.Interferon type 1 (IFN‐1) production and signaling is associated with the acquisition of therapy resistance, following chronic DNA damage, via Interferon‐related DNA damage resistance signature (IRDS) gene expression. An alternative, DNA damage‐independent role of sustained IFN‐1 mediated resistance was identified and characterized by the emergence of ...
Ashlyn Conant +11 more
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Benchmarking Outlier Detection Methods for Detecting IEM Patients in Untargeted Metabolomics Data
Metabolites, 2023 Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM).
Michiel Bongaerts +9 more
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FEBS Open Bio, EarlyView.Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
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Adaptive threshold based outlier detection on IoT sensor data: A node-level perspective
Alexandria Engineering JournalThe accuracy and reliability of IoT-based sensor networks depend on validating sensed data, including detecting outliers at the node level. This study proposes an online outlier detection approach using Multiple Linear Regression-based adaptive ...
M. Veera Brahmam, S. Gopikrishnan
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FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
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IEEE Access, 2017 In this paper, we propose an novel interactive outlier detection system called feature-rich interactive outlier detection (FRIOD), which features a deep integration of human interaction to improve detection performance and greatly streamline the ...
Xiaodong Zhu +5 more
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EXTENDED APPLIED DATA CLEANING METHODS IN OUTLIER DETECTION FOR RESIDENTIAL CONSUMER [PDF]
Carpathian Journal of Electrical Engineering, 2023 This paper delves into the subject of outlier detection techniques tailored for unique datasets related to residential energy consumption. Building upon the current state of research we introduce the Grubbs and Z-score methods and investigate a range of ...
Dacian I. JURJ +7 more
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