AIMC Topic: Monte Carlo Method

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Spin-transfer torque magnetic memory as a stochastic memristive synapse for neuromorphic systems.

IEEE transactions on biomedical circuits and systems
Spin-transfer torque magnetic memory (STT-MRAM) is currently under intense academic and industrial development, since it features non-volatility, high write and read speed and high endurance. In this work, we show that when used in a non-conventional...

Artificial neural network modelling of biological oxygen demand in rivers at the national level with input selection based on Monte Carlo simulations.

Environmental science and pollution research international
Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to report annual BOD values to Eur...

Comparison of 3D and 4D Monte Carlo optimization in robotic tracking stereotactic body radiotherapy of lung cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: To investigate the adequacy of three-dimensional (3D) Monte Carlo (MC) optimization (3DMCO) and the potential of four-dimensional (4D) dose renormalization (4DMCrenorm) and optimization (4DMCO) for CyberKnife (Accuray Inc., Sunnyvale, CA) ra...

Modelling personal exposure to particulate air pollution: an assessment of time-integrated activity modelling, Monte Carlo simulation & artificial neural network approaches.

International journal of hygiene and environmental health
An experimental assessment of personal exposure to PM10 in 59 office workers was carried out in Dublin, Ireland. 255 samples of 24-h personal exposure were collected in real time over a 28 month period. A series of modelling techniques were subsequen...

Adaptive Cardiorespiratory Separation With Harmonic Models and Filters: The Case of Electrical Impedance Tomography.

IEEE transactions on bio-medical engineering
Cardiorespiratory monitoring methods are vital in clinical and personal healthcare contexts, continuously delivering comprehensive insights into patient health. Among them, electrical impedance tomography, a non-invasive imaging modality, uniquely en...

Advancing wetland groundwater pollution zoning: A novel integration of Monte Carlo health risk modeling and machine learning.

Journal of hazardous materials
Wetlands serve as crucial water reservoirs, providing essential water resources for the surrounding regions. However, elevated ion concentrations in wetland groundwater may pose health risks to local populations. This study focused on Judian Lake and...

Machine learning-based estimation of occupational radiation dose in interventional cardiology.

Radiation protection dosimetry
In interventional cardiology, occupational radiation exposure for medical personnel can reach high levels, underscoring the critical need for effective radiation protection and monitoring methods. This study employs machine learning algorithms to est...

Assessing Uncertainty in Machine Learning for Polymer Property Prediction: A Benchmark Study.

Journal of chemical information and modeling
Machine learning (ML) has emerged as a transformative tool in material science, enabling accelerated discovery and design of novel molecules while reducing experimental costs. Uncertainty quantification (UQ) is crucial for enhancing the reliability o...