There are many studies in the scientific literature that present predictions from parametric statistical models based on maximum likelihood estimates of the unknown parameters. However, generating predictions from maximum likelihood parameter estimat...
Modern software systems need to autonomously adapt their behavior at runtime in order to maintain their utility in response to continuous environmental changes. Most studies on models at runtime focus on providing suitable techniques to manage the co...
Reliable assessment of prediction reliability is important in biomedical sensing and measurement applications, where machine learning models increasingly transform imaging, physiological, chemical, and molecular measurements into clinically relevant...
Software reliability is prioritised as the most critical quality attribute. Reliability prediction models participate in the prevention of software failures which can cause vital events and disastrous consequences in safety-critical applications or e...
The failure of different chips under working conditions is influenced by various stress states such as different voltages, temperatures, stress durations, and stress variations. Therefore, the failure time has a great degree of dispersion, and simila...
With improvements in the computing capability of edge devices and the emergence of edge computing, an increasing number of services are being deployed on the edge side, and container-based virtualization is used to deploy services to improve resource...
Loading and unloading truss robot for computer numerical control (CNC) punch is widely used in the production of sheet metal parts, as its reliability level is directly related to the quality of sheet metal parts. Especially for the automatic sheet m...
This paper addresses the challenges of life prediction and reliability assessment for ball screws under complex operating conditions by proposing a reliability prediction model that incorporates full-life fatigue damage. First, a full-life fatigue li...
For the sake of conducting distribution network reliability prediction in an accurate and efficient manner, a model for distribution network reliability prediction (IAO-LSSVM) based on an improved Aquila Optimizer (IAO) optimized mixed-kernel Least S...
Software reliability prediction is commonly performed using parametric software reliability growth models, but their forecasting accuracy depends strongly on whether the assumed mean value function is suitable for the observed fault-detection process...
For satellite electronic components characterized by high reliability and long lifespan, achieving improved efficiency in reliability prediction is essential when only a limited amount of data is available. Many studies have collected degradation dat...
Reliable prediction of abutment scour requires accurate point estimates and quantification of predictive uncertainty. This study developed a NGBoost (Natural Gradient Boosting) framework using 297 laboratory observations under clear-water conditions...
Two main factors, including regression accuracy and adversarial attack robustness, of six trajectory prediction models are measured in this paper using the traffic flow management system (TFMS) public dataset of fixed-wing aircraft trajectories in a...
As sensor monitoring technology continues to evolve, structural online monitoring and health management have found numerous applications across various fields. However, challenges remain concerning the real-time diagnosis of structural damage and the...
The communication module is crucial for control systems. Under thermal, electrical, and mechanical stresses, sensitive digital and analog components may degrade in performance or fail, compromising the module’s long-term stability. Existing rel...
When a wearable gait predictor is personalized to a new user, a short calibration session may contain missing channels, sensor-placement changes, electrode shift, noise, fatigue, or other non-ideal effects. Treating all calibration samples as equally...
To achieve the low-cycle fatigue (LCF) lifetime prediction and reliability estimation of turbine blisks, a Marine Predators Algorithm (MPA)-based Kriging (MPA-Kriging) method is developed by introducing the MPA into the Kriging model. To obtain the o...
Online hotel reviews provide a major source of information for understanding guest satisfaction, yet rating prediction remains difficult because review text is often short, highly skewed toward positive scores, and affected by inconsistent or repetit...
Predicting concrete carbonation depth is essential for durability design and life-cycle management of concrete bridges. This study combines a physics-informed neural network with a calibrated ensemble of classical learners to estimate the carbonation...
Rolling element bearings are critical components in rotating machinery, yet assessing and predicting their reliability under heavy industrial noise remains challenging. Existing methods suffer from three major limitations: (1) single-channel signal p...
This study proposes a hybrid computational framework that integrates the Extended Finite Element Method (XFEM), Artificial Neural Network (ANN), and Monte Carlo simulation to evaluate the fatigue crack propagation and reliability of reinforced concre...
Unmanned aerial vehicle (UAV) scanning and mobile laser scanning provide detailed three-dimensional observations for forest inventory and structural monitoring for which point-wise separation of ground, understory, woody components, and foliage is fu...
Background: Selecting informative training samples is a fundamental yet challenging problem in predictive modeling, particularly in heterogeneous clinical data. Although supervised learning is typically formulated as an optimization problem over mode...
AlGaN-based deep ultraviolet light-emitting diodes (DUV LEDs) have been widely deployed in water treatment, sterilization, and optical communication owing to their intrinsic merits of mercury-free operation, compact footprint, and fast turn-on capabi...
In the design of military, automotive, medical, space, and professional equipment, it is essential to demonstrate that devices can operate for a specific duration with a given level of confidence. Reliability must be considered in the design process,...
Reliability prediction of aerospace dormant components requires fusing natural-storage observations at the operating temperature with accelerated-storage testing data at elevated temperatures. Existing scalar-weight fusion methods apply a global weig...
In the last decade, a higher level of reliability has become a compulsory demand when it comes to modern DC-DC converters. This work addresses the main reliability metrics: in many studies, the failure rate λ and MTBF of an output capacitor ba...
This paper presents a new methodical procedure to monitor in real time the junction temperature of SiC Power MOSFET modules of parallel-connected chips utilized in machine drive systems to develop their reliability modelling and predict their lifetim...
As district heating networks age, current asset management practices, such as those relying on static life expectancies and age- and rule-based approaches, need to be replaced by data-driven asset management. As an alternative to physics-of-failure m...
Recommender systems aspire to provide users with recommendations that have a high probability of being accepted. This is accomplished by producing rating predictions for products that the users have not evaluated, and, afterwards, the products with t...
This paper presents the use of proportional hazards regression models for predicting the Mean Time Between Failures (MTBF) of centrifugal pumps in the oil and gas industry. To that end, a dataset collected over 8 years including both design and opera...
A 96-channel (50 GHz-spacing) athermal AWG has been developed. It has a wide operating range due to reduced temperature dependence than conventional AWG. The temperature dependence of the center wavelength of the developed module satisfied the &plusm...
In this paper, AE signals collected during fatigue crack-growth of aluminum and titanium alloys (Al7075-T6 and Ti-6Al-4V) were analyzed and compared. Both the aluminum and titanium alloys used in this study are prevalent materials in aerospace struct...
Robotic systems have become a standard tool in modern manufacturing due to their unique characteristics, such as repeatability, precision, and speed, among others. One of the main challenges of robotic manipulators is the low degree of reliability. L...
This paper introduces a novel Bayesian Fractional Weibull (BFW) regression framework, which generalizes the classical Weibull accelerated failure time model using fractional calculus. The proposed methodology addresses key challenges in big data reli...
The reliability of ocean-going ship engine fuel systems is crucial for the safety and continuous operation of vessels. Failure of this system can lead to serious operational and economic consequences; therefore, effective diagnostics and failure pred...
The increasing demand for reliable and efficient power electronic systems in critical applications—such as renewable energy, electric vehicles, and aerospace—has intensified the need to understand and predict failure mechanisms in power d...
We have developed a 17-channel (150 GHz-spacing) athermal arrayed waveguide grating (AAWG), which has a wider operation range than that of the existing AWGs, by designing a metal structure assembly that reduces the temperature dependence of the wavel...
Machine learning results based on radiomic analysis are often not transferrable. A potential reason for this is the variability of radiomic features due to varying human made segmentations. Therefore, the aim of this study was to provide comprehensiv...
Based on the “Future Outlook” sections of annual and semi-annual reports from Chinese A-share-listed companies (2011–2024), we construct a novel measure of managerial confidence by quantifying the intertemporal shifts in textual sen...
The objective of this study was to compare the proportion of explained genetic variance (EXGV) and the reliability of genomic breeding values (GBVs) predictions for milk yield (MY), fat yield (FY), protein yield (PY) fat percentage (FP), protein perc...
This paper reviews recent progress in fault detection, reliability analysis, and predictive maintenance methods for grid-connected solar photovoltaic (PV) systems. With the rising adoption of solar power globally, maintaining system reliability and p...
This study formulates predictive maintenance of complex technical systems as a constrained multi-layer probabilistic optimization problem that unifies four interdependent analytical paradigms. The mathematical framework integrates: (i) Weibull reliab...
The non-homogeneous Poisson process (NHPP) software has a crucial role in computer systems. Furthermore, the software is used in various environments. It was developed and tested in a controlled environment, while real-world operating environments ma...
Conventional methods for calculating sortie mission reliability of shipborne vehicle layouts suffer from excessive computational overhead, long runtimes, and large labeled data requirements. To address these limitations, this work proposes a speciali...
Blockchain is an innovative distributed ledger technology that is widely used to build next-generation applications without the support of a trusted third party. With the ceaseless evolution of the service-oriented computing (SOC) paradigm, Blockchai...
The objective of this study is to quantify how independently degraded operational-data quality affects predictive accuracy, predictive uncertainty, and prediction-level eligibility for decision support in AI-enabled aviation energy management. The ev...
The distributed nature of IoT systems and new trends focusing on fog computing enforce the need for reliable communication that ensures the required quality of service for various scenarios. Due to the direct interaction with the real world, failure...
Hybrid automatic repeat request (HARQ) remains the backbone of link-layer reliability, yet it was designed for a setting in which every bit matters equally and the channel of the next slot is unknown. Neither assumption holds in semantic communicatio...
Radiation-induced transient faults pose a growing challenge for safety-critical embedded systems, yet traditional radiation testing and large-scale statistical fault injection (SFI) remain costly and impractical during early design stages. This paper...
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