Results 61 to 70 of about 1,015,115 (264)
Pattern classification for incomplete data [PDF]
KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2002 The problem of pattern classification for inputs with missing values is considered. A general fuzzy min-max (GFMM) neural network utilising hyperbox fuzzy sets as a representation of data cluster prototypes is used. It is shown how a classification decisions can be carried out on a subspace of high dimensional input data.
openaire +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Ewing sarcoma (ES) and rhabdomyosarcoma (RMS) are aggressive malignancies in children and adolescents where metastases impact prognosis. 18F‐fluoro‐2‐deoxy‐d‐glucose positron emission tomography/computed tomography (FDG‐PET/CT) and bone marrow aspirate and trephine biopsies (BMAT) are used to identify disease involvement.
Imogen Andrews +3 more
wiley +1 more source
Chengshi guidao jiaotong yanjiu[Objective] To address the issues of prediction delay and accuracy degradation caused by incomplete deformation monitoring data in metro foundation pits, a prediction method based on a CNN-GRU (convolutional neural network-gated recurrent unit) neural ...
ZHOU Yi +5 more
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Robustness of the Data-Driven Identification algorithm with incomplete input data [PDF]
Journal of Theoretical, Computational and Applied MechanicsIdentifying the mechanical response of a material without presupposing any constitutive equation is possible thanks to the Data-Driven Identification algorithm developed by the authors.
Marie Dalémat +3 more
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
EnergiesAccurate estimation of the state of health (SOH) of lithium-ion batteries is crucial for battery management systems (BMS), as it directly affects system safety, operational reliability, and remaining useful life prediction.
Le Ke, Xiangbo Zhang, Lujuan Dang
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FEBS Letters, EarlyView.We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley +1 more source
GrImp: Granular Imputation of Missing Data for Interpretable Fuzzy Models
AxiomsData 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
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Calpain small subunit homodimerization is robust and calcium‐independent
FEBS Letters, EarlyView.Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy +4 more
wiley +1 more source
KFCM-PSOTD : An Imputation Technique for Missing Values in Incomplete Data Classification
Cauchy: Jurnal Matematika Murni dan AplikasiData mining is a very important process for finding out the data interpretation. Data preprocessing is the crucial data mining steps. The existence of missing values in the data is one of the primary issues with data preprocessing. Generally, this can be
Muhaimin Ilyas +2 more
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