We explore an exchangeably weighted bootstrap of the general function-indexed empirical U-processes in the Markov setting, which is a natural higher-order generalization of the weighted bootstrap empirical processes. As a result of our findings, a co...
In a general Markov decision progress system, only one agent’s learning evolution is considered. However, considering the learning evolution of a single agent in many problems has some limitations, more and more applications involve multi-agent...
The goal of this research is to maximize chord-based composition possibilities given a relatively small amount of information. A transformational approach, based in group theory, was chosen, focusing on chord intervals as the components of a modified...
Generally, these days people live longer but often with increased impairment and disabilities; therefore, they can benefit from assistive technologies. In this paper, we focus on the completion of activities of daily living (ADLs) by such patients, u...
The performance of urban bridges will deteriorate gradually throughout service life. Bridge deterioration prediction is essential for bridge management, especially for maintenance planning and decision-making. By considering the time-dependent reliab...
We propose a Markov Decision Process Model that blends ideas from Psychological research and Economics to study decision-making in individuals with self-control problems. We have borrowed a dual-process of decision-making with self-awareness from Psy...
This article investigates the zonotope-based state estimation for boost converter system with Markov jump process. DC-DC boost converters are pivotal in modern power electronics, enabling renewable energy integration, electric vehicle charging, and m...
Today, there are a wide variety of ways to produce goods in a manufacturing company. Among the most common are mass or line production and process production, both of which are antagonists. In an online production system, materials move from station...
A Bayesian approach was developed, tested, and applied to model ordinal response data in monotone non-decreasing processes with measurement errors. An inhomogeneous hidden Markov model with continuous state-space was considered to incorporate measure...
The mixture of Gaussian process functional regressions (GPFRs) assumes that there is a batch of time series or sample curves that are generated by independent random processes with different temporal structures. However, in real situations, these str...
China imports a large quantity of bauxite each year. Bauxite in fine particles with high moisture has a high risk of liquefaction during the maritime transportation process, which is harmful to the stability and safety of the carrier. To ensure safe...
Maintenance decision-making is essential to achieve safe and reliable operation with high performance for equipment. To avoid unexpected shutdown and increase machine life as well as system efficiency, it is fundamental to design an effective mainten...
Corrosion is one of the major causes of failure in pipelines for transporting oil and gas products. To mitigate the impact of this problem, organizations perform different maintenance operations, including detecting corrosion, determining corrosion g...
Human-Computer Interaction (HCI) research has extensively employed eye-tracking technologies in a variety of fields. Meanwhile, the ongoing development of Internet Protocol TV (IPTV) has significantly enriched the TV customer experience, which is of...
LEO satellite mega-constellation projects have been proposed by many countries or commercial organizations in recent years. With more than 2000 satellites launched by SpaceX to configure the Starlink system, the orbital resources are more constrained...
In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possi...
A remarkably high growth has been observed in the uses of wireless sensor networks (WSNs), due to their momentous potential in various applications, namely the health sector, smart agriculture, safety systems, environmental monitoring, military opera...
In the context of distributed defense, multi-sensor networks are required to be able to carry out reasonable planning and scheduling to achieve the purpose of continuous, accurate and rapid target detection. In this paper, a multi-sensor cooperative...
We define a class of Markov cell processes,
Federated Learning (FL), as an emerging paradigm in distributed machine learning, has received extensive research attention. However, few works consider the impact of device mobility on the learning efficiency of FL. In fact, it is detrimental to the...
The Analytic Hierarchy Process (AHP) has been a widely used multi-criteria decision-making (MCDM) method since the 1980s because of its simplicity and rationality. However, the conventional AHP assumes criteria independence, which is not always accur...
Renewable energy systems dominated by powered electronic devices generally exhibit weak disturbance tolerance and limited grid-support capability. Following the blocking of a flexible DC transmission system, emergency load shedding in renewable-rich...
Picking the reflection horizon is an important step in velocity inversion and seismic interpretation. Manual picking is time-consuming and no longer suitable for current large-scale seismic data processing. Automatic algorithms using different seismi...
During the last decades, collaborative robots capable of operating out of their cages are widely used in industry to assist humans in mundane and harsh manufacturing tasks. Although such robots are inherently safe by design, they are commonly accompa...
The design optimization of the grading of a resonator array for energy harvesting in sensors is described. Attention is paid to set the resonator heights, possibly removing resonators whenever convenient. Instead of employing time-consuming heuristic...
Hidden Markov model (HMM) is a vital model for trajectory recognition. As the number of hidden states in HMM is important and hard to be determined, many nonparametric methods like hierarchical Dirichlet process HMMs and Beta process HMMs (BP-HMMs) h...
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 deal with backward stochastic differential equations driven by a pure jump Markov process and an independent Brownian motion (BSDEJs for short). We start by proving the existence and uniqueness of the solutions for this type of equation and presen...
Recently, studies on early-exit mechanisms have emerged to reduce the computational cost during the inference process of deep learning models. However, most existing early-exit architectures simply determine early exiting based only on a target confi...
Inducing learning strategies is a crucial component of intelligent tutoring systems. Previous research has predominantly focused on the induction of offline learning strategies. Although the existing offline learning strategy induction methods can al...
This paper introduces a pioneering model that merges coupled Markov chains (CMC) with the fuzzy analytic hierarchy process (FAHP) to enhance multi-criteria decision making (MCDM) amidst the dynamic interplay of criteria. Traditional MCDM frameworks o...
An approach based on the hidden Markov model (HMM) is proposed for risk performance reasoning (RPR) for the bauxite shipping process by Handy carriers. The unobservable (hidden) state process in the approach aims to model the underlying risk performa...
Online multi-object tracking (MOT) has broad applications in time-critical video analysis scenarios such as advanced driver-assistance systems (ADASs) and autonomous driving. In this paper, the proposed system aims at tracking multiple vehicles in th...
The location of user equipment (UE) should always be maintained in order to connect any incoming calls within a mobile network. While several methods of location registration have been proposed, most mobile networks have adopted zone-based registrati...
In order to connect an incoming call to the user equipment (UE) in a mobile communication network, the location information of the UE must be always kept in the network database. Therefore, the efficiency of the location registration method of report...
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The multimode underwater acoustic communication network is a novel form of underwater acoustic communication that adjusts its communication mode to enhance overall performance. Current performance analysis methods are primarily applied to single-mode...
The introduction of medical Internet of Things (IoT) for biomedical applications has brought about the era of proactive healthcare. Such advanced medical supervision lies on the foundation of a network of energy-constrained wearable or implantable se...
Many path planning algorithms developed for land or air based autonomous vehicles no longer apply under the water. A time-optimal path planning method for autonomous underwater vehicles (AUVs), based on a Markov decision process (MDP) algorithm, is p...
Whether for institutional investors or individual investors, there is an urgent need to explore autonomous models that can adapt to the non-stationary, low-signal-to-noise markets. This research aims to explore the two unique challenges in quantitati...
The visual analysis of trajectory topics is helpful for mining potential trajectory patterns, but the traditional visual analysis method ignores the evolution of the temporal coherence of the topic. In this paper, a novel visual analysis method for d...
The Ka-band and higher Q/V band channels can provide an appealing capacity for the future deep-space communications and Space Information Networks (SIN), which are viewed as a primary solution to satisfy the increasing demands for high data rate serv...
Autonomous vehicles (AVs) are increasingly operating in complex traffic environments where safe and efficient decision-making is crucial. Merging into roundabouts is a key interaction scenario. This paper introduces a decision-making approach for rou...
A real-time path planning algorithm based on the Markov decision process (MDP) is proposed in this paper. This algorithm can be used in dynamic environments to guide the wheeled mobile robot to the goal. Two phases (the utility update phase and the p...
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...
This research paper presents studies on the operation process of the Honker 2000 light utility vehicles that are part of the Polish Armed Forces transport system. The phase space of the process was identified based on the assumption that at any given...
We discuss Markov edge processes
This paper shows that Harris recurrent Markov chains and processes can be characterized as the class of Markov chains and processes for which there exists a random time T at which the distribution of the chain or process does not depend on its initia...
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...
This work focuses on optimizing energy dispatch in a hydroelectric power plant (HPP) with a large number of generating units (GUs) and uncertainties caused by sediment accumulation in the water intakes. The study was realized at Jirau HPP, and integr...
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