This study extracted the featured vectors in the same way from testing data and substituted these vectors into a trained hidden Markov model to get the log likelihood probability. The log likelihood probability was matched with the time–probabi...
13 July 2021
Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natu...
With the development of intelligent transportation, vehicle motion state recognition has become a crucial method for enhancing the reliability of vehicle navigation and ensuring driving safety. Currently, machine learning is the main approach for rec...
Long-term GEO satellite operation requires reliability models that distinguish full mission capability from degraded but still functional states and from critical functional loss. This study develops a five-state Markov reliability model in which sta...
Misfolding and aggregation of transthyretin (TTR) is widely known to be responsible for a progressive systemic disorder called amyloid transthyretin (ATTR) amyloidosis. Studies suggest that TTR aggregation is initiated by a rate-limiting dissociation...
RNA polymerases are essential enzymes that catalyze DNA transcription into RNA, vital for protein synthesis, gene expression regulation, and cellular responses. Non-template-dependent RNA polymerases, which synthesize RNA without a template, are valu...
This paper presents an investigation of the condition state distribution and performance condition curve of the transformer population under different pre-determined maintenance repair rates based on the Markov Prediction Model (MPM). In total, 3195...
The formation of neurofibrillary tangles (NFT) with β-sheet-rich structure caused by abnormal aggregation of misfolded microtubule-associated protein Tau is a hallmark of tauopathies, including Alzheimer’s Disease. It has been reported tha...
Kirsten rat sarcoma viral oncogene homolog (KRAS) is a small GTPase protein which plays an important role in the treatment of KRAS mutant cancers. The FDA-approved AMG510 and MRTX849 (phase III clinical trials) are two potent KRASG12C-selective inhib...
Pilots’ loss of situational awareness is one of the human factors affecting aviation safety. Numerous studies have shown that pilot perception errors are one of the main reasons for a lack of situational awareness without a proper system to det...
Rare, but important, transition events between long-lived states are a key feature of many molecular systems. In many cases, the computation of rare event statistics by direct molecular dynamics (MD) simulations is infeasible, even on the most powerf...
There are multiple ways in which a stochastic system can be out of statistical equilibrium. It might be subject to time-varying forcing; or be in a transient phase on its way towards equilibrium; it might even be in equilibrium without us noticing it...
This work presents a method to improve the diagnostic performance of empirical classification system (ECS), which is used to estimate the degradation state of components based on measured signals. The ECS is embedded in a homogenous continuous-time,...
Poor recognition of delirium among hospitalized elderlies is a typical challenge for health care professionals. Considering methodological insufficiency for assessing time-varying diseases, a continuous-time Markov multi-state transition model (CTMMT...
Inflammation is a protective stress response triggered by external stimuli, with 5-lipoxygenase (5LOX) playing a pivotal role as a potent mediator of the leukotriene (Lts) inflammatory pathway. Nordihydroguaiaretic acid (NDGA) functions as a natural...
Mutations in leucine-rich repeat kinase 2 (LRRK2) are recognized as the most frequent cause of Parkinson’s disease (PD). As a multidomain ROCO protein, LRRK2 is characterized by the presence of both a Ras-of-complex (ROC) GTPase domain and a kinase d...
We present a two-country model (North and South) that describes the phenomenon of offshoring and reshoring. The model is a continuous time-controlled Markov chain with binary states. The main trade-off involves production costs and transaction costs...
When studying Markov chain models and semi-Markov chain models, it is useful to know which state vectors
The accurate inference of hidden states from non-stationary physiological signals remains a significant challenge in stochastic process modeling. This paper proposes an Adaptive Sticky Hidden Markov Model (Sticky-HMM) framework designed to enhance th...
As a member of the fatty acids transporter family, the heart fatty acid binding proteins (HFABPs) are responsible for many important biological activities. The binding mechanism of fatty acid with FABP is critical to the understanding of FABP functio...
This paper proposes a continuous state partially observable Markov decision process (POMDP) model for the corrosion maintenance of oil and gas pipelines. The maintenance operations include complex and extensive activities to detect the corrosion type...
We use the representation of a continuous time Hattendorff differential equation and Matlab to compute
Advances in image processing technologies have provided more precise views in medical and health care management systems. Among many other topics, this paper focuses on several aspects of video-based monitoring systems for elderly people living indep...
A real-time, metadata-driven electric vehicle routing optimization to reduce on-road energy requirements is proposed in this work. The proposed strategy employs the state–action–reward–state–action (SARSA) algorithm to learn t...
Power system health prognosis is a key process of condition-based maintenance. For the problem of large error in the residual lifetime prognosis of a power system, a novel residual lifetime prognosis model based on a high-order hidden semi-Markov mod...
The problem of robust state estimation for a class of uncertain nonlinear systems with Markov jump is investigated. The uncertain nonlinear system under consideration is represented by the Takagi–Sugeno (T–S) fuzzy model because it is dif...
In this paper, in order to enhance the autonomous operation capabilities of aircraft and ensure their operational safety and efficiency, we propose an autonomous decision-making framework based on target motion state prediction combined with the Mark...
We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the Susceptible-Infectious-Recovered (SIR)-type epidemiological model that we developed for viral disease...
Polyphenol oxidase (PPO) plays a key role in the enzymatic browning process, and this study employed Gaussian-accelerated molecular dynamics (GaMD) simulations to investigate the catalytic efficiency mechanisms of lotus root PPO with different substr...
Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application of HMM in trading stocks (with S&P 500 index being an example...
Accurate acquisition of the spatiotemporal distribution of urban forests and fragmentation (e.g., interior and intact regions) is of great significance to contributing to the mitigation of climate change and the conservation of habitat biodiversity....
The technical condition of bridges has become a crucial issue for organizing the maintenance and repairs in bridge management systems. It is of great practical engineering significance to construct an effective model for predicting the technical cond...
This study presents a five-state functional model for assessing the reliability of electric vehicle charging infrastructure from the perspective of charging-service capability. The model distinguishes full functionality, three levels of degradation,...
This paper aims to determine the Markovian pattern of the factors influencing social deprivation in Mexicans with Type 2 diabetes mellitus (DM2). To this end, we develop a methodology to meet the theoretical and practical considerations involved in a...
Over the past decade, Markov State Models (MSM) have emerged as powerful methodologies to build discrete models of dynamics over structures obtained from Molecular Dynamics trajectories. The identification of macrostates for the MSM is a central deci...
Current fuzzing techniques for industrial control protocols (ICPs) encounter notable challenges, including model training instability, limited sample diversity, and the inability to manage complex state dependencies in protocol interactions. To addre...
State sequence analysis of longitudinal categorical data seeks to synthesize pathways through different dimensions of the life course for descriptive, associative and predictive purposes. Given the number and variety of patterns in such data, measure...
Future stock prices depend on many internal and external factors that are not easy to evaluate. In this paper, we use the Hidden Markov Model, (HMM), to predict a daily stock price of three active trading stocks: Apple, Google, and Facebook, based on...
Precise and real-time estimation of the robotic arm’s position on the patient’s side is essential for the success of remote robotic surgery in Tactile Internet (TI) environments. This paper presents a prediction model based on the Transfo...
To effectively guarantee a secure and stable operation of a smart substation, it is essential to develop a relay protection system considering the real-time online operation state evaluation and the risk assessment of that substation. In this paper,...
This study aimed to explore the state transition of regional innovation capacity (RIC) and analyze the heterogeneous effects of determinants in an innovative subject and environment of RIC state transition based on the data collected from 30 province...
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain&rsquo...
Demand Response (DR) provides an opportunity for customers to reduce their loads during times of high prices and therefore to shave the peak loads. The power outputs of large-scale generator units can be predicted and controlled easily; therefore, th...
In this study, we present a state-based diagnostic and prognostic methodology for lubricating oil degradation based on a nonparametric Bayesian approach, i.e., sticky hierarchical Dirichlet process–hidden Markov model (HDP-HMM). An accurate health st...
Many interesting rare events in molecular systems, like ligand association, protein folding or conformational changes, occur on timescales that often are not accessible by direct numerical simulation. Therefore, rare event approximation approaches li...
Activating mutations in the epidermal growth factor receptor (EGFR) are key oncogenic drivers across multiple cancers, yet the structural mechanisms by which these mutations promote persistent receptor activation remain elusive. Here, we investigate...
In this study we develop a multi-factor extension of the family of Lee-Carter stochastic mortality models. We build upon the time, period and cohort stochastic model structure to extend it to include exogenous observable demographic features that can...
As the number and capacity of photovoltaic (PV) power stations increase, it is of great significance to evaluate the PV-connected power systems in an effective, reasonable, and quick way. In order to overcome the challenge of PV’s time-sequenti...
APLNR is a therapeutically important G protein-coupled receptor (GPCR) implicated in cardiovascular and metabolic regulation; however, how agonist binding reorganizes receptor dynamics to promote signaling competence remains poorly understood. Here,...
Lung cancer remains one of the leading causes of death worldwide due to its high rates of illness and mortality. In this study, we applied a continuous-time multi-state Markov model to examine how lung cancer progresses through six clinically defined...
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