Results 141 to 150 of about 14,276,290 (299)
A study on learning-augmented k-means clustering
reservedClustering is a practical approach for extracting meaningful information from unstructured data. With the exponential growth of data, it is essential to develop efficient methods for computing clusters.
PEPAJ, MARIA TERESA
core
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
FT K-Means: A High-Performance K-Means on GPU with Fault Tolerance
2024 IEEE International Conference on Cluster Computing (CLUSTER)K-means is a widely used algorithm in clustering, however, its efficiency is primarily constrained by the computational cost of distance computing. Existing implementations suffer from suboptimal utilization of computational units and lack resilience against soft errors.
Shixun Wu +10 more
openaire +3 more sources
Intrusion detection system using hybird gsa-k-means [PDF]
, 2013 Security is an important aspect in our daily life. Intrusion Detection Systems (IDS) are developed to be the defense against security threats. Current signature based IDS like firewalls and antiviruses, which rely on labeled training data, generally ...
Aslahi Shahri, Bibi Masoomeh
core
Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions
FEBS Letters, EarlyView.The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang +4 more
wiley +1 more source
Global k-means++: an effective relaxation of the global k-means clustering algorithm
Applied IntelligenceThe $k$-means algorithm is a prevalent clustering method due to its simplicity, effectiveness, and speed. However, its main disadvantage is its high sensitivity to the initial positions of the cluster centers. The global $k$-means is a deterministic algorithm proposed to tackle the random initialization problem of k-means but its well-known that ...
Georgios Vardakas, Aristidis Likas
openaire +3 more sources
, 2014 One of techniques popular inData Mining is clustering. Defenition clustering in scientific from data miningis some of data or objectsin one group or clusters into cluster so each cluster will containthedataas closely aspossibleanddifferent objects in ...
Nainggolan, Rena
core
Semesta Teknika, 2016 The selection process among outstanding students in a department has a big problem. This process is not fair because only involve one criteria and ignore the other criteria.
Asroni Asroni, Ronald Adrian
doaj
A review of unsupervised k-value selection techniques in clustering algorithms
Journal of Industrial Engineering and ManagementPurpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms, which makes them an essential tool when working with large datasets. However, although they are unsupervised tools, they generally require
Ana Pegado-Bardayo +3 more
doaj +1 more source
An epithelial GPR35 isoform supports tumor‐associated transcriptional and metabolic phenotypes
FEBS Letters, EarlyView.GPR35 generates two functionally distinct isoforms with previously unresolved roles. GPR35‐short mediates immune‐cell chemotaxis, while GPR35‐long is enriched in colorectal cancer epithelium, where it supports increased metabolism, proliferation, and tumor‐associated transcriptional programs.
Jørgen D. Rønneberg +14 more
wiley +1 more source