Results 111 to 120 of about 11,198,909 (310)
Federated learning is a technique that enables the use of distributed datasets for machine learning purposes without requiring data to be pooled, thereby better preserving privacy and ownership of the data. While supervised FL research has grown substantially over the last years, unsupervised FL methods remain scarce.
Swier Garst, Marcel J. T. Reinders
openaire +2 more sources
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
Clustering dichotomously scored items through functional k-means algorithm
, 2016 In the educational field, it is common to analyze the probability of a correct response to a test item as a continuous function of the item parameters and the subject ability. This relation is given by the item response function.
Di Battista, Tonio; Dipartimento di Metodi Quantitativi e Teoria Economica, Università "G. d'Annunzio" Chieti-Pescara +1 more
core +1 more source
pH‐mediated activation of the lysosomal arginine sensor SLC38A9
FEBS Letters, EarlyView.Cells monitor nutrient levels via the lysosomal transporter SLC38A9 to activate the mechanistic target of rapamycin complex 1 (mTORC1). This study reveals that SLC38A9 function is regulated by pH. We identified histidine 544 as a critical pH sensor that undergoes conformational changes to control amino acid efflux from lysosomes; therefore, it ...
Xuelang Mu, Ampon Sae Her, Tamir Gonen
wiley +1 more source
Skill set profile clustering: the empty K-means algorithm with automatic specification of starting cluster centers [PDF]
, 2010 While students’ skill set profiles can be estimated with formal cognitive diagnosis models [8], their computational complexity makes simpler proxy skill estimates attractive [1, 4, 6].
Nugent, R., Ayers, E., Dean, N.
core
Implementasi KD-Tree K-Means Clustering untuk Klasterisasi Dokumen
Jurnal Teknik ITS, 2013 Klasterisasi dokumen adalah suatu proses pengelompokan dokumen secara otomatis dan unsupervised. Klasterisasi dokumen merupakan permasalahan yang sering ditemui dalam berbagai bidang seperti text mining dan sistem temu kembali informasi.
Eric Budiman Gosno +2 more
doaj
FEBS 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
Pengenalan Pola Citra Penyakit Pada Daun Tanaman Padi Menggunakan GCLM dan Algoritma K-Means
, 2018 Penelitian ini bertujuan untuk mengidentifikasi penyakit pada daun tanamanpadi dan membantu penyuluh mengenali penyakit yang ada pada daun tanaman padidengan pola citra menggunakan metode GLCM untuk fitur ekstraksi dan AlgoritmaK-Means untuk ...
Lilis Indriani, Zahir Zainuddin, Ingrid
core
Optimisation of Criminal Data Clustering Model using Information Gain
Journal of Innovation Information Technology and ApplicationCrime is a phenomenon that significantly impacts society, necessitating mapping efforts that can be utilized for further analysis. Clustering, as a data analysis technique, groups objects based on similarities or differences in their characteristics ...
Prih Diantono Abda’u +3 more
doaj
The human gut microbiome across the life course
FEBS 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