Differential quadrature method (DQM) for a class of singular two-point
Differential quadrature method is applied in this work to solve singular two-point boundary value problems with a linear or non-linear nature. It is demonstrated through numerical examples that accurate results for the problem with different types of boundary conditions can be obtained using a considerably small number of grid points.
Yucel, U, Sari, M
openaire +1 more source
A High-Performance Solid-State Secondary Battery Using a Triple-Phase-Interface Anode Displaying Excellent Capacity and Electrochemical Kinetics. [PDF]
Huang X +9 more
europepmc +1 more source
Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection. [PDF]
Asres MW +6 more
europepmc +1 more source
Lysozyme-dequalinium encapsulation in a Zn-Fe LDH-chia seed matrix for enhanced antimicrobial dental therapeutics. [PDF]
Mahgoub SM +9 more
europepmc +1 more source
The CMS Data Quality Monitoring software experience and future improvements
The Data Quality Monitoring (DQM) Software proved to be a central tool in the CMS experiment. Its flexibility allowed its integration in several environments Online, for real-time detector monitoring; Offline, for the final, fine-grained Data ...
De Guio, Federico
core
Frequent Missed Opportunities for Earlier Diagnosis of Advanced-Stage Colorectal or Lung Cancer. [PDF]
Zimolzak AJ +12 more
europepmc +1 more source
Application of a digital quality measure for cancer diagnosis in Epic Cosmos. [PDF]
Zimolzak AJ +3 more
europepmc +1 more source
Nonlocal Strain Gradient Model for the Nonlinear Static Analysis of a Circular/Annular Nanoplate. [PDF]
Sadeghian M, Palevicius A, Janusas G.
europepmc +1 more source
Atmospheric mercury monitoring data across Italy: A multi-year national dataset (2020 - 2023). [PDF]
Bencardino M +14 more
europepmc +1 more source
DEEP CONTINUAL LEARNING FOR ANOMALY DETECTION IN PARTICLE PHYSICS EXPERIMENTS
Data quality monitoring (DQM) is the process of identifying usable data in par- ticle physics experiments. Automation of the DQM process can lead to substan- tially improved data quality with considerably reduced human effort.
Drage Steen, Eirik
core

