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
Physics, Multidisciplinary
Anand N. Vidyashankar, Jeffrey F. Collamore
Summary: This article analyzes the probabilities of rare events induced by Hellinger distance using large deviation theory under potential model misspecifications. The probabilities are found to decay exponentially, with the decay characterized by a rate function expressed as a convex conjugate of a limiting cumulant generating function. Geometric considerations arising from the analysis facilitate an explicit representation, even in cases where the limiting generating function is nondifferentiable.
Article
Computer Science, Artificial Intelligence
Guangtao Ran, Zhan Shu, Hak-Keung Lam, Jian Liu, Chuanjiang Li
Summary: This article addresses the problem of multiple-event-triggered dissipative tracking control for nonlinear Markov jump systems with incomplete transition probabilities. It proposes a methodology involving two adaptive event-triggered schemes for the actuator and sensor channels. By using a fuzzy model and a hidden Markov model, the underlying nonlinearities and possible asynchronous phenomenon are captured. The desired tracking controller is established based on the Lyapunov and dissipativity theory.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Engineering, Civil
Kai Cheng, Iason Papaioannou, Zhenzhou Lu, Xiaobo Zhang, Yanping Wang
Summary: This paper proposes a sequential directional importance sampling (SDIS) method for rare event estimation. The method expresses a small failure probability in terms of a sequence of auxiliary failure probabilities, estimated using Monte Carlo simulation and directional importance sampling. The method outperforms existing sequential sampling reliability methods, as demonstrated by experiments.
Article
Engineering, Chemical
Vikram Sudarshan, Warren D. Seider, Amish J. Patel, Ulku G. Oktem, Jeffrey E. Arbogast
Summary: An advisory system is developed in this paper to analyze and recognize highly unanticipated and randomly occurring abnormal events in chemical and manufacturing plants. The system utilizes novel multivariate alarm systems and response actions, along with process modeling and path-sampling techniques. This system aims to enhance the existing safety/reliability systems by suggesting appropriate actions when approaching unanticipated abnormal events.
Article
Engineering, Civil
P-R Wagner, S. Marelli, I Papaioannou, D. Straub, B. Sudret
Summary: Estimating the probability of rare failure events is crucial for reliability assessment of engineering systems. The stochastic spectral embedding (SSER) method improves the local approximation accuracy of global, spectral surrogate modelling techniques by sequentially embedding local residual expansions in subdomains of the input space. It decomposes the failure probability into a set of easy-to-compute conditional failure probabilities. The proposed modifications to the algorithm enhance its efficiency in solving rare event estimation problems.
Article
Computer Science, Information Systems
Qi Zhang, Carla Seatzu, Zhiwu Li, Alessandro Giua
Summary: The study focuses on the problem of state estimation in partially-observed discrete event systems subject to cyber attacks. An operator observes a plant through a natural projection and aims to estimate the current state of the system, while an attacker can tamper with the observations to alter the state estimation. A joint estimator automaton is defined to describe all possible attacks, showing the joint state estimation for each possible corrupted observation.
Article
Computer Science, Information Systems
Shitong Cui, Le Liu, Wei Xing, Xudong Zhao
Summary: This paper addresses the problem of remote state estimation in a linear discrete invariant system using a smart sensor for measurements and local estimates, with communication based on event scheduling in the smart sensor. The MMSE estimator is introduced and Gaussian preserving event-based sensor scheduling is used to strike a balance between communication cost and estimation quality. The variation range of communication probability is calculated to aid in designing the event-triggered estimation policy, and simulation results demonstrate the effectiveness of the proposed event-triggered estimator.
Review
Chemistry, Analytical
Justas Furmonas, John Liobe, Vaidotas Barzdenas
Summary: Event-based cameras are gaining popularity in the commercial space and have great potential for depth estimation. However, research on event-based camera depth estimation is still limited. This work provides an analysis and summary of existing methods and systems, and offers recommendations for further research.
Article
Automation & Control Systems
Jun Cheng, Jiangming Xu, Ju H. H. Park, Michael V. V. Basin
Summary: This article focuses on load frequency control for interconnected multiarea power systems (IMAPSs) with nonhomogeneous sojourn probabilities (NSPs) and cyber-attacks. A generalized framework of NSPs is formulated to describe the dynamic behavior of IMAPSs. To govern variations of sojourn probabilities, a deterministic switching signal is introduced using the average dwell-time technique. An improved event-triggered protocol relevant to the dynamic quantizer parameter is presented to increase triggering intervals. Both denial-of-service and deception attacks, following Bernoulli distributions, are considered during information transmission. The mean-square exponential stability of the considered systems is established using the Lyapunov theory. The effectiveness of the obtained results is verified through a numerical example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Robotics
Hebert Azevedo-Sa, Suresh Kumaar Jayaraman, Connor T. Esterwood, X. Jessie Yang, Lionel P. Robert, Dawn M. Tilbury
Summary: Issues of trust miscalibration between drivers and self-driving vehicles can be addressed through dynamic modeling and estimation of trust levels using various sensed behaviors, with a proposed framework integrating eye-tracking signals, system usage time, and performance on non-driving tasks. Results from a study with simulated automated driving systems show the success of the approach in computing trust estimates, encouraging the use of strategies for modeling and estimating trust in automated driving systems to design trust-aware systems.
INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS
(2021)
Editorial Material
Environmental Sciences
A. Gupta, R. S. Govindaraju, R. Morbidelli, C. Corradini
Summary: Bayes theorem provides a framework for parameter estimation by combining prior and sample information, but the availability and vagueness of prior knowledge may require the use of a reference prior for objective analysis. This study pursues an information-theoretic approach to derive reference priors and compares them to results obtained using a uniform prior.
WATER RESOURCES RESEARCH
(2022)
Article
Computer Science, Information Systems
Xudong Wang, Guoqi Wang, Zhe Li, Zhongyang Fei
Summary: In this paper, a fault estimation and compensation approach is proposed for discrete-time systems with event-triggered scheme based on zonotope techniques. By introducing dynamic interval variables, a component-wise dynamic event-triggered strategy is utilized to reduce the consumption of communication resources. A joint state-fault estimator is constructed to estimate the system state and faults simultaneously, and a co-design approach of the estimator, compensator, and event-triggered strategy is proposed to guarantee stability and performance. Simulation results on aircraft engine systems demonstrate the effectiveness of the designed method in fault estimation and fault tolerance.
INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Xiaoguang Han, Jinliang Wang, Zhiwu Li, Xiaoyan Chen, Zengqiang Chen
Summary: This paper presents a new perspective on state estimation and weak detectability verification for discrete event systems. Two new matrix-based information structures are constructed using the semi-tensor product technique for computing different types of state estimates. The concept of weak delayed detectability is introduced, and various detectability problems are discussed. The proposed approaches are numerically tractable and can be implemented algorithmically. Examples are provided to illustrate the obtained results.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Industrial
Yu Zhang, You Dong, Dan M. Frangopol
Summary: This paper proposes a new stopping criterion for the adaptive Kriging model with SDMCS, aiming to reduce the computational effort while maintaining accuracy in reliability analysis.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Mathematical & Computational Biology
Min K. Roh, Bernie J. Daigle
BMC SYSTEMS BIOLOGY
(2016)
Article
Biochemical Research Methods
Bernie J. Daigle, Min K. Roh, Linda R. Petzold, Jarad Niemi
BMC BIOINFORMATICS
(2012)
Article
Mathematical & Computational Biology
Min K. Roh, Philip Eckhoff
BMC SYSTEMS BIOLOGY
(2014)
Article
Biology
Min K. Roh
BULLETIN OF MATHEMATICAL BIOLOGY
(2019)
Article
Chemistry, Physical
Dan T. Gillespie, Min Roh, Linda R. Petzold
JOURNAL OF CHEMICAL PHYSICS
(2009)
Article
Chemistry, Physical
Min K. Roh, Dan T. Gillespie, Linda R. Petzold
JOURNAL OF CHEMICAL PHYSICS
(2010)
Article
Chemistry, Physical
Min K. Roh, Bernie J. Daigle, Dan T. Gillespie, Linda R. Petzold
JOURNAL OF CHEMICAL PHYSICS
(2011)
Article
Infectious Diseases
Dennis L. Chao, Anna Roose, Min Roh, Karen L. Kotloff, Joshua L. Proctor
PLOS NEGLECTED TROPICAL DISEASES
(2019)
Proceedings Paper
Mathematics, Applied
Min K. Roh, Joshua L. Proctor
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2016 (ICNAAM-2016)
(2017)