Results 41 to 50 of about 9,620,800 (176)
ABSTRACT This study examines how plastics manufacturing firms can be classified according to their level of implementation of circular economy (CE) and industrial symbiosis (IS) practices and how such adoption influences sustainability performance. Using data from plastics manufacturing firms, we integrate cluster analysis with partial least squares ...
Laura Cristina Ramírez‐Rodríguez +3 more
wiley +1 more source
Manhattan Distance-based K-Medoids Clustering Improvement for Diagnosing Diabetic Disease
Diabetes is a metabolic disorder characterized by blood glucose levels above normal limits. Diabetes occurs when the body is unable to produce sufficient insulin to regulate blood sugar levels.
Solikhun +3 more
doaj +1 more source
ABSTRACT The rapid digital transformation of financial services, increasing regulatory pressure and the growing strategic relevance of sustainability are reshaping financial intermediaries and how they are perceived by younger generations. In this context, traditional monetary compensation schemes are increasingly insufficient to explain how financial ...
Gerardo Petroccione +2 more
wiley +1 more source
Prediction of LVEF improvement in patients with HFrEF and HFmrEF following treatment with Sacubitril/Valsartan. Workflow of this study investigating the functional capacity improvement in response to Sacubitrail/Valsartsan in a real‐world scenario of heart failure treatment.
Florian Appenzeller +8 more
wiley +1 more source
Comparison Of K-Means and K-Medoids Algorithm for Clustering Data UMKM in Pagar Alam City
The aim of this research is clustering MSME data in Pagar Alam City using the K-Means and K-Medoids algorithms. This research is motivated by the lack of further management of MSME data collection, which can hinder the development and improvement of ...
sendy ariska +2 more
doaj +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Perbandingan Analisis Segmen Pelanggan Perusahaan Logistik Dengan Clustering K-Means dan K-Medoids [PDF]
Hasil analisis menunjukkan perbedaan distribusi dan karakteristik masing-masing cluster antara algoritma K-Means dan K-Medoids. K-Means menghasilkan cluster dengan variasi yang lebih besar, sedangkan K-Medoids menghasilkan cluster yang lebih terfokus ...
Tesalonika, Tesalonika
core +1 more source
Energy‐Flow Regimes and Their Temporal Transitions in a PV‐Building System
Unlike production and consumption, which act as external factors, generated energy flows reflect the system's internal behavior regarding energy allocation at each time step. The combination of self‐consumption, surplus, and import of surplus energy into the power grid characterizes how electricity is routed between the building's local consumption and
Jacek Caban +3 more
wiley +1 more source
Joint Risk Factor Combinations with Additive Interaction Increase the Risk of Parkinson's Disease
Abstract Background Combined effects of multiple risk factors on incident late‐onset Parkinson's disease (PD; LOPD) remain poorly characterized. Objective The objective of this study was to quantify the impact of joint risk exposures and estimate the contribution of potentially modifiable factors to incident LOPD risk.
Andrea Quattrone +5 more
wiley +1 more source
Identification of groups in k-medoids clustering approach.
Identification of groups in k-medoids clustering approach.
Ian S. McRae (396921) +5 more
core +1 more source

