A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis
Alzheimer's disease (AD) is a complex form of dementia and due to its high phenotypic
variability, its diagnosis and monitoring can be quite challenging. Biomarkers play a crucial …
variability, its diagnosis and monitoring can be quite challenging. Biomarkers play a crucial …
A review of clustering algorithms: comparison of DBSCAN and K-mean with oversampling and t-SNE
E Bajal, V Katara, M Bhatia… - Recent Patents on …, 2022 - ingentaconnect.com
The two most widely used and easily implementable algorithm for clustering and
classification-based analysis of data in the unsupervised learning domain are Density …
classification-based analysis of data in the unsupervised learning domain are Density …
An integrated assessment framework of economic, environmental, and human health impacts using scan-to-BIM and life-cycle assessment in existing buildings
The significance of environmental management of existing buildings in reducing the
environmental impact of the construction sector is increasingly emphasized. However, life …
environmental impact of the construction sector is increasingly emphasized. However, life …
A framework for fault detection and diagnostics of articulated collaborative robots based on hybrid series modelling of Artificial Intelligence algorithms
A Polenghi, L Cattaneo, M Macchi - Journal of Intelligent Manufacturing, 2024 - Springer
Smart factories build on cyber-physical systems as one of the most promising technological
concepts. Within smart factories, condition-based and predictive maintenance are key …
concepts. Within smart factories, condition-based and predictive maintenance are key …
A comprehensive evaluation of OPTICS, GMM and K-means clustering methodologies for geochemical anomaly detection connected with sample catchment basins
The process of data-driven clustering to uncover geochemical anomalies linked to sample
catchment basins (SCBs) includes a comprehensive framework to discern areas exhibiting …
catchment basins (SCBs) includes a comprehensive framework to discern areas exhibiting …
A spatiotemporal study and location-specific trip pattern categorization of shared e-scooter usage
This study analyzes the temporally resolved location and trip data of shared e-scooters over
nine months in Berlin from one of Europe's most widespread operators. We apply time …
nine months in Berlin from one of Europe's most widespread operators. We apply time …
[HTML][HTML] Learning human-process interaction in manual manufacturing job shops through indoor positioning systems
F Pilati, A Sbaragli - Computers in Industry, 2023 - Elsevier
Nowadays, manufacturing systems are increasingly embracing the Industry 4.0 paradigm.
Therefore, manual and low-standardized manufacturing environments are often digitized …
Therefore, manual and low-standardized manufacturing environments are often digitized …
Increasing the precision of public transit user activity location detection from smart card data analysis via spatial–temporal DBSCAN
FC Ozer, H Tuydes-Yaman, G Dalkic-Melek - Data & Knowledge …, 2024 - Elsevier
Smart Card (SC) systems have been increasingly adopted by public transit (PT) agencies all
over the world, which facilitates not only fare collection but also PT service analyses and …
over the world, which facilitates not only fare collection but also PT service analyses and …
Goal-oriented clustering algorithm to monitor the efficiency of logistic processes through real-time locating systems
F Pilati, A Sbaragli, T Ruppert… - International Journal of …, 2024 - Taylor & Francis
Modern internal logistic systems face several challenges, from supply chain disruption to
mass customization of marketed products. In such a highly dynamic scenario, Internet of …
mass customization of marketed products. In such a highly dynamic scenario, Internet of …
Scalable and robust outlier detector using hierarchical clustering and long short-term memory (lstm) neural network for the internet of things
RM Shukla, S Sengupta - Internet of Things, 2020 - Elsevier
The emerging centralized entities, like cloud, edge, or Software-Defined Network (SDN),
make automated decisions for the Internet of Things (IoT) applications based on the …
make automated decisions for the Internet of Things (IoT) applications based on the …