Results 1 to 10 of about 4,392,224 (352)

Automated terrestrial laser scanning with near-real-time change detection – monitoring of the Séchilienne landslide [PDF]

open access: yesEarth Surface Dynamics, 2017
We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals ...
R. A. Kromer   +10 more
doaj   +1 more source

Comparing Flow-R, Rockyfor3D and RAMMS to Rockfalls from the Mel de la Niva Mountain: A Benchmarking Exercise

open access: yesGeosciences, 2023
Rockfall simulations are often performed at various levels of detail depending on the required safety margins of rockfall-hazard-related assessments. As a pseudo benchmark, the simulation results from different models can be put side-by-side and compared
François Noël   +6 more
doaj   +1 more source

Model-driven transformation and validation of adaptive educational hypermedia using CAVIAr [PDF]

open access: yes, 2010
Authoring of Adaptive Educational Hypermedia is a complex activity requiring the combination of a range of design and validation techniques.We demonstrate how Adaptive Educational Hypermedia can be transformed into CAVIAr courseware validation models ...
Melia, Mark, Pahl, Claus
core   +2 more sources

Research on Construction Risk Management of Underground Engineering Based on AHP-Fuzzy Comprehensive Evaluation Method [PDF]

open access: yesE3S Web of Conferences, 2021
In order to strengthen the construction risk management of underground engineering projects, reduce the probability of accidents, and ensure that the underground engineering completes the construction tasks on schedule, the article relies on a certain ...
Han Zhichao, Zhu Jun, Wang Jianduo
doaj   +1 more source

Security engineering risk analysis (SERA) [PDF]

open access: yesProceedings of the 3rd International Workshop on Software Engineering Research and Industrial Practice, 2016
In this presentation, I describe how the SEI’s Security Engineering Risk Analysis (SERA) method provides a structure that connects desired system functionality with the underlying software to evaluate the sufficiency of requirements for software security and the potential operational security risks based on mission impact.
openaire   +1 more source

Quantifying the effectiveness of early warning systems for natural hazards [PDF]

open access: yesNatural Hazards and Earth System Sciences, 2016
Early warning systems (EWSs) are increasingly applied as preventive measures within an integrated risk management approach for natural hazards. At present, common standards and detailed guidelines for the evaluation of their effectiveness are lacking. To
M. Sättele, M. Bründl, D. Straub
doaj   +1 more source

Real-Time Characterization of Finite Rupture and Its Implication for Earthquake Early Warning: Application of FinDer to Existing and Planned Stations in Southwest China

open access: yesFrontiers in Earth Science, 2021
Earthquake early warning (EEW) not only improves resilience against the risk of earthquake disasters, but also provides new insights into seismological processes.
Jiawei Li   +4 more
doaj   +1 more source

Using Peak and Cumulative Spinal Loading to Assess Jobs, Job Rotation and Engineering Controls [PDF]

open access: yes, 2003
Peak and cumulative forces on spinal structures have been identified as significant and statistically independent risk factors for reporting low back pain (LBP).
Frazer, Mardy B
core   +2 more sources

Machine Learning for Long COVID Inference Based on the Acute Phase: A Case Study in Healthcare Professionals

open access: yesIEEE Access
Since 2021, the COVID-19 pandemic has affected global health, economies, and societal structures, leading to great attention to new research and awareness.
Caio B. S. Maior   +4 more
doaj   +1 more source

An investigation of belief-free DRL and MCTS for inspection and maintenance planning

open access: yesJournal of Infrastructure Preservation and Resilience
We propose a novel Deep Reinforcement Learning (DRL) architecture for sequential decision processes under uncertainty, as encountered in inspection and maintenance (I &M) planning.
Daniel Koutas   +2 more
doaj   +1 more source

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