Results 31 to 40 of about 92,800 (264)

Empowering Retail in the Metaverse by Leveraging Consumer Behavior Analysis for Personalized Shopping: A Pilot Study in the Saudi Market

Journal of Theoretical and Applied Electronic Commerce Research
The integration of advanced technologies, such as the Metaverse, has the potential to revolutionize the retail industry and enhance the shopping experience. Understanding consumer behavior and leveraging machine learning predictions based on analysis can
Monerah Alawadh, Ahmed Barnawi
doaj   +1 more source

Characterizing Situations of Dock Overload in Bicycle Sharing Stations

Applied Sciences, 2018
Bicycle sharing systems are becoming increasingly popular in cities around the world as they are an inexpensive and sustainable means of transportation.
Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Giuseppe Ricupero, Elena Baralis   +5 more
doaj   +1 more source

niarules: Advancing interpretable machine learning through numerical association rule mining and 3D coral plot visualization

SoftwareX
Numerical association rule mining remains comparatively underexplored in interpretable machine learning, largely due to the challenges of handling continuous variables and the limited availability of effective visualization techniques.
Iztok Fister Jr, Gerlinde Emsenhuber, Jan Hendrik Plümer, Iztok Fister, Andreas Holzinger   +4 more
doaj   +1 more source

Dietary Protein Intake and Peritoneal Protein Losses in Peritoneal Dialysis Patients

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction Peritoneal dialysis (PD) patients lose protein in their waste dialysate, potentially increasing their risk for malnutrition. We wished to determine whether there was any association between losses and dietary protein intake (DPI). Methods DPI was assessed from 24‐h dietary recall using Nutrics software.
Haalah Shaaker, Andrew Davenport
wiley   +1 more source

Executive Control in Learning: Evidence for the Dissociation of Rule Learning and Associative Learning

Advances in Cognitive Psychology, 2019
The dual-process account and the propositional account of learning hold opposite views regarding the recruitment of higher-level processes in rule learning and associative learning. Taking an individual differences perspective, the current study focused on the relationship between rule learning and associative learning and investigated to what extent ...
Wang, Tengefi, Schweizer, Karl, Ren, Xuezhu   +2 more
openaire   +2 more sources

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Efficiency of Local Learning Rules in Threshold-Linear Associative Networks [PDF]

Physical Review Letters, 2020
We show that associative networks of threshold linear units endowed with Hebbian learning can operate closer to the Gardner optimal storage capacity than their binary counterparts and even surpass this bound. This is largely achieved through a sparsification of the retrieved patterns, which we analyze for theoretical and empirical distributions of ...
Francesca Schönsberg, Yasser Roudi, Alessandro Treves   +2 more
openaire   +3 more sources

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, Basak Bahcivanci, Antonietta Hayhoe, Animesh Acharjee, Ezgi Özkurt   +4 more
wiley   +1 more source

Scalable multi-metric association rule learning for explainable book recommendations

Frontiers in Computer Science
Digital reading platforms have grown rapidly, increasing information overload and highlighting the need for efficient and transparent recommendation systems.
Adel Hidri, Suleiman Ali AlSaif, Eman AlShehri, Minyar Sassi Hidri   +3 more
doaj   +1 more source

Efficient learning of microbial genotype–phenotype association rules [PDF]

Bioinformatics, 2010
AbstractMotivation: Finding biologically causative genotype–phenotype associations from whole-genome data is difficult due to the large gene feature space to mine, the potential for interactions among genes and phylogenetic correlations between genomes.
Norman J. MacDonald, Robert G. Beiko
openaire   +2 more sources