Article
Engineering, Mechanical
Mohsen Rashki
Summary: The proposed SESC method is derived from the control variate technique and estimates a quick imprecise failure probability before refining the estimation and directing samples towards the important failure region. Unlike conventional SubSim, the performance of SESC is not affected by the geometry of the performance function away from the limit state surface.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Chemistry, Physical
Lucy Ham, Megan A. Coomer, Michael P. H. Stumpf
Summary: Modeling and simulation of complex biochemical reaction networks are important in modern biophysics. This study presents a computational simulation method to investigate the stochastic dynamics of biochemical systems subject to both intrinsic and extrinsic noise. The method accurately captures the first two moments of the stationary probability density while significantly reducing computational runtime. It provides a practical and efficient approach to study systems affected by multiple noise sources simultaneously.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Physics, Multidisciplinary
Samaneh Gholami, Silvana Ilie
Summary: Stochastic modeling of biochemical processes at the cellular level has gained significant attention in recent years. This paper proposes a technique for detecting collinearity among parameters in mathematical models and applies it to select subsets of parameters that can be estimated accurately. The method is successfully tested on several practical models of biochemical systems.
Article
Engineering, Industrial
Guofa Li, Tianzhe Wang, Zequan Chen, Jialong He, Xiaoye Wang, Xuejiao Du
Summary: This study proposes a new method, RBIK-SS, which combines the reliability analysis method based on importance sampling and k-medoids clustering with subset simulation, to estimate small failure probabilities. The method replaces the MCS sample pool in RBIK with a smaller SS population to overcome memory limitations. The results show that RBIK-SS can solve rare failure events with satisfactory accuracy and efficiency.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Chemical
Yongjie Chen, Jue Ding, Xi Xia, Peifen Weng
Summary: The proposed time-driven Monte Carlo method based on weighted particles shows promising agreement with analytical solutions for both binary and multi-breakage cases, resolving particle size distribution with lower statistical noise and being suitable for long-time simulations. Its accuracy is less dependent on weighted particle number or time increment.
Article
Physics, Fluids & Plasmas
Ernesto Berrios-Caro, Tobias Galla
Summary: The proposed tau-leaping simulation algorithm captures environmental noise beyond the adiabatic limit, achieving good performance in the regime of fast environmental dynamics. It retains environmental stochasticity to subleading order and requires significantly less computing time compared to full simulations of the combined system and environment.
Article
Computer Science, Interdisciplinary Applications
Yiming Che, Ziqi Guo, Changqing Cheng
Summary: Stochastic kriging (SK) provides an explicit way to characterize heterogeneous noise variance in stochastic computer simulations, but relies on tedious Monte Carlo (MC) method. Therefore, researchers have developed efficient stochastic kriging informed by generalized polynomial chaos (gPC-SK) to reduce computational costs.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Automation & Control Systems
Zhaoqiang Ge
Summary: This paper discusses the exact observability and stability of stochastic implicit systems. Conditions for the existence and uniqueness of impulse solutions, necessary and sufficient conditions for exact observability, and stability conditions are derived using stochastic Laplace transform, matrix theory, and linear matrix inequalities. Examples are provided to illustrate the effectiveness of the theoretical results.
SYSTEMS & CONTROL LETTERS
(2021)
Article
Computer Science, Interdisciplinary Applications
Alessio Lapolla, Aljaz Godec
Summary: The paper introduces an algorithm for computing the non-Markovian time-dependent conditional probability density function of a tagged-particle in a single-file system of N diffusing particles. By implementing an eigenexpansion through the coordinate Bethe ansatz, the algorithm reduces the complexity from O(N!) to O(N) by exploiting exchange symmetries between the particles.
COMPUTER PHYSICS COMMUNICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Sandro K. Otani, Thalyta T. Martins, Sergio R. Muniz, Paulo C. de Sousa Filho, Fernando A. Sigoli, Rene A. Nome
Summary: In this study, we use stochastic dynamics and nonlinear optical simulations to investigate the non-equilibrium trajectories of individual Yb (III):Er (III) colloidal particles driven by two-dimensional dynamic optical traps. We also analyze the effects of fluctuations at the single-particle level by examining position trajectories and time-dependent upconversion emission intensities.
FRONTIERS IN CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Eberhard O. Voit, Daniel V. Olivenca
Summary: Choosing the most suitable representations is crucial for biomedical systems analysis. Ordinary differential equations (ODEs) are the most prevalent choice due to their flexibility and ease of use. However, selecting a mathematical format for the equations is not trivial and often lacks objective guidance. Power-law approximations are simple and overcome limitations in describing nonlinear features of biomedical phenomena. Nonetheless, ODE models also have limitations, leading to the proposal of an alternative approach called discrete Biochemical Systems Theory (dBST).
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Engineering, Mechanical
M. Aswathy, C. O. Arun
Summary: A novel and simple stochastic meshfree method is proposed for the stochastic eigenvalue analysis of problems in structural mechanics. The method models Young's modulus as a homogeneous random field, using both truncated normal and lognormal distribution characteristics. By modifying the Monte Carlo simulation on the system of equations, this method provides an accurate and more efficient evaluation of stochastic eigensolutions.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Management
Jonas Andersson, Filip Malmberg, Johan Marklund
Summary: This paper presents a method for analyzing the inventory level distribution in a centralized inventory system with quantity restricted deliveries. The study shows the importance of considering quantitative delivery restrictions when optimizing reorder points in multi-echelon systems to avoid high backorder costs and inadequate customer service.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Saadat M. Alhashmi, Ahmed M. Khedr, Ifra Arif, Magdi El Bannany
Summary: This study presents sentiment analysis of two critical events using machine learning techniques, proposing a hybrid classification approach and showing its advantages in performance, with four main contributions.
Article
Mathematics, Applied
Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann
Summary: The estimation of the probability of rare events is essential in reliability and risk assessment, especially when dealing with failure events expressed in terms of a limit-state function. Approximations of the exact solution to the partial differential equation are used to estimate the probability of rare events, introducing approximation errors. The relationship between the required accuracy of the probability estimate and the level of PDE discretization is crucial for guiding reliability analyses and multilevel methods.
SIAM JOURNAL ON NUMERICAL ANALYSIS
(2021)
Review
Microbiology
Adaoha E. C. Ihekwaba, Ivan Mura, Pradeep K. Malakar, John Walshaw, Michael W. Peck, G. C. Barker
JOURNAL OF BACTERIOLOGY
(2016)
Article
Immunology
Adaoha E. C. Ihekwaba, Ivan Mura, Michael W. Peck, G. C. Barker
PATHOGENS AND DISEASE
(2015)
Article
Biochemical Research Methods
Adaoha E. C. Ihekwaba, Ivan Mura, John Walshaw, Michael W. Peck, Gary C. Barker
PLOS COMPUTATIONAL BIOLOGY
(2016)
Article
Microbiology
Paola Lecca, Ivan Mura, Angela Re, Gary C. Barker, Adaoha E. C. Ihekwaba
FRONTIERS IN MICROBIOLOGY
(2016)
Article
Mathematical & Computational Biology
Adaoha E. C. Ihekwaba, Ivan Mura, Gary C. Barker
BMC SYSTEMS BIOLOGY
(2014)
Article
Environmental Sciences
Ivan Mura, Juan Felipe Franco, Laura Bernal, Nicolas Melo, Juan Jose Diaz, Raha Akhavan-Tabatabaei
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2020)
Article
Computer Science, Interdisciplinary Applications
Juan Jose Diaz, Ivan Mura, Juan Felipe Franco, Raha Akhavan-Tabatabaei
Summary: The aiRe air quality data analysis tool, based on the R statistical framework and Shiny web package, helps city managers to better address air quality issues, improve local capabilities, and promote decision-making. This tool simplifies the process of data analysis and visualization, reduces costs, increases accessibility, and enhances decision-making abilities for both the public and governmental authorities.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Computer Science, Hardware & Architecture
Kun Qiu, Zheng Zheng, Kishor S. Trivedi, Ivan Mura
Summary: This article examines the threat of Mandelbug-caused software failures to system availability and proposes methods to improve system availability, such as developing an analytic model and a tool for calculating system availability. The research demonstrates that recovery methods based on environmental diversity can effectively enhance system availability.
IEEE TRANSACTIONS ON RELIABILITY
(2021)
Article
Green & Sustainable Science & Technology
Diego A. Sierra, Juan F. Rueda, Camilo Mejia-Moncayo, Ivan Mura, Felipe Munoz
Summary: This article proposes a method to support expert decision-making in designing the layout of chemical plants. The method uses the Bacterial Foraging Algorithm to determine the allocation of main process units in a two-dimensional space, with the goal of minimizing total cost. Fire and explosion hazards are assessed using Dow's Fire and Explosion Index. The proposed method allows for flexibility in considering both safety and economic aspects, while providing high-quality solutions in reduced computation time.
PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Diego Sierra, Juan Briceno, Hector Buitrago, Brian Rozo, Leonardo Montecchi, Ivan Mura
2018 EIGHTH LATIN-AMERICAN SYMPOSIUM ON DEPENDABLE COMPUTING (LADC)
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Daniela Azumendi Gongora, Juan Jose Diaz Baquero, Juan Felipe Franco, Ivan Mura
2018 WINTER SIMULATION CONFERENCE (WSC)
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Camilo Mejia-Moncayo, Alix E. Rojas, Ivan Mura
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2018, PT I
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Daniela Angulo Diaz, Raha Akhavan-Tabatabaei, Ivan Mura
2016 WINTER SIMULATION CONFERENCE (WSC)
(2016)
Article
Computer Science, Theory & Methods
I. Mura, D. Prandi, C. Priami, A. Romanel
ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE
(2009)
Article
Environmental Sciences
Juan F. Franco, Julian F. Segura, Ivan Mura
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2016)