Results 141 to 150 of about 13,094,494 (259)

Analisis Karakteristik Mahasiswa Berdasarkan Nilai Kelompok Mata Kuliah dengan Menggunakan Analisis Cluster K-Means [PDF]

open access: yes, 2019
Indeks Prestasi (IP) adalah nilai yang dihitung berdasarkan jumlah beban studi yang diambil dalam satu semester dikalikan dengan bobot prestasi tiap-tiap mata kuliah kemudian dibagi dengan jumlah beban kredit yang diambil. IPK merupakan IP kumulatif dari
Yahdin, Sugandi   +2 more
core   +1 more source

Diversity and complexity in neural organoids

open access: yesFEBS Letters, EarlyView.
Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley   +1 more source

America means "I love you, my yankee land" [PDF]

open access: yes, 1917
For voice and piano.Caption title.On score verso: A-M-E-R-I-C-A means "I love you, my yankee land" / words and music by Jack Frost. Frank K.
Graham, Roger, 1885-1938.
core  

Performance of standard k-means, sparse k-means and randomized k-means algorithms for clustering KIRC tumor cell grades.

open access: yes, 2015
Performance of standard k-means, sparse k-means and randomized k-means algorithms for clustering KIRC tumor cell grades.
Junhai Jiang (773105)   +3 more
core   +1 more source

Residual tail twisting in ascidian larvae is stabilized by asymmetric myofibrils that resist bilateral symmetry restoration

open access: yesFEBS Letters, EarlyView.
Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure   +3 more
wiley   +1 more source

FT K-Means: A High-Performance K-Means on GPU with Fault Tolerance

open access: yes2024 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

The human gut microbiome across the life course

open access: yesFEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero   +4 more
wiley   +1 more source

Penerapan Metode K-Means Untuk Clustering Mahasiswa Berdasarkan Nilai Akademik Dengan Weka Interface Studi Kasus Pada Jurusan Teknik Informatika UMM Magelang

open access: yesSemesta 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  

Global k-means++: an effective relaxation of the global k-means clustering algorithm

open access: yesApplied Intelligence
The $k$-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

A K-means-like algorithm for informetric data clustering

open access: yes, 2015
The K-means algorithm is one of the most often used clustering techniques. However, when it comes to discovering clusters in informetric data sets that consist of non-increasingly ordered vectors of not necessarily conforming lengths, such a method ...
Anna Cena (13497691)   +1 more
core  

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