Results 51 to 60 of about 559,125 (302)
Making Roasted Mutton Colourimetric Card Based on Machine Vision Technology
Shipin gongye ke-ji, 2022 In order to establish a standardized method that can quickly and nondestructively identify the color changes in the process of mutton roasting, this study combined three algorithms (mean value algorithm, K-means algorithm and K-means+image noise ...
Bo WANG +3 more
doaj +1 more source
An efficient approach based on differential evolution algorithm for data clustering [PDF]
Decision Science Letters, 2014 Clustering plays an essential role for data analysis and it has been widely used in different fields like data mining, machine learning and pattern recognition.
Maryam Hosseini +2 more
doaj +1 more source
Applied Sciences, 2022 Metaheuristic algorithms have been hybridized with the standard K-means to address the latter’s challenges in finding a solution to automatic clustering problems.
Abiodun M. Ikotun, Absalom E. Ezugwu
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing autoimmune disease of the central nervous system. High‐dose intravenous methylprednisolone (IVMP) is the standard first‐line therapy for acute attacks, although some patients remain refractory.
Wataru Horiguchi +5 more
wiley +1 more source
Color image segmentation using a spatial k-means clustering algorithm [PDF]
, 2006 This paper details the implementation of a new adaptive technique for color-texture segmentation that is a generalization of the standard K-Means algorithm. The standard K-Means algorithm produces accurate segmentation results only when applied to images
Ilea, Dana E., Whelan, Paul F.
core
FEBS Letters, EarlyView.Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
K-means algorithms for functional data [PDF]
Neurocomputing, 2015 Cluster analysis of functional data considers that the objects on which you want to perform a taxonomy are functions f : X e Rp ↦R and the available information about each object is a sample in a finite set of points f ¼ fðx ; y ÞA X x Rgn .
López García, María Luz +2 more
openaire +2 more sources
An optimized initialization center K-means clustering algorithm based on density
, 2015 Traditional K-means algorithm's clustering effect is affected by the initial cluster center points. To solve this problem, a method is proposed to optimize the K-means initial center points.
Xiaofeng Zhou +5 more
core +1 more source
Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
FEBS Letters, EarlyView.A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
FEBS Letters, EarlyView.An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley +1 more source