This review discusses a simple family of models capable of simulating tropical cyclone life cycles, including intensification, the formation of the axisymmetric version of boundary layer shocks, and the development of an eyewall. Four models are disc...
Predicting the susceptibility of a specific part of a landslide (SSPL) involves predicting the likelihood that the part of the landslide (e.g., the entire landslide, the source area, or the scarp) will form in a given area. When predicting SSPL, the...
Building energy-use models and tools can simulate and represent the distribution of energy consumption of buildings located in an urban area. The aim of these models is to simulate the energy performance of buildings at multiple temporal and spatial...
Despite its effectiveness in determining breakage function parameters (BFPs) for quantifying breakage characteristics in mineral grinding processes, the back-calculation method has limitations owing to the uncertainty regarding the distribution of th...
Mass balance measurements for Golubin glacier in Northern Tien Shan, Kyrgyzstan, have been discontinuous over the last century, with significant data gaps. We provide a unique over 100-year-long mass balance series on daily resolution. We applied a t...
Data security and user privacy concerns are receiving increasing attention. Federated learning models based on differential privacy offer a distributed machine learning framework that protects data privacy. However, the noise introduced by the differ...
Turbulent flows over forest canopies have been successfully modeled using Large-Eddy Simulations (LES). Simulated winds result from the balance between a simplified pressure gradient forcing (e.g., a constant pressure-gradient or a canonical Ekman ba...
Previous scoring models, such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) score, do not adequately predict the mortality of patients receiving mechanical ventilation in the intensive care unit. Therefore, this stu...
Coastal and hydraulic structures, such as revetments, embankments and levees—as well as their underlying soil—may experience piping when exposed to outward pressure gradients. The aim of the present study is twofold: (1) to derive the for...
This paper is devoted to the modelling of nonlocality in continuum physics through constitutive functions that depend on suitable gradients. For definiteness, the attention is addressed to elastic solids, heat conductors, and magnetic solids. Models...
The secondary use of electronic health records is essential for developing artificial intelligence-based clinical decision support systems. However, even after direct identifiers are removed, de-identified electronic health records remain vulnerable...
Federated learning (FL), as a distributed learning mechanism, can have model training completed without directly uploading original data, effectively reducing the risk of privacy leakage. However, through the shared gradient information, research sho...
Neural network training often suffers from spectral asymmetry, where gradient energy is disproportionately allocated to high-frequency components, leading to suboptimal convergence and reduced efficiency. This paper introduces Gradient Spectral Norma...
Aerodynamic/stealth optimization is a key issue during the design of a stealth UAV. Balancing the weight of different incident angles of the RCS and combining stealth characteristics with aerodynamic characteristics are hotspots of aerodynamic/stealt...
To address the challenge of collaborative strategy optimization caused by non-independent and identically distributed data in cross-institutional scenarios, a federated quantitative learning framework integrating Path Attention Aggregation Module (PA...
Using a three-dimensional, hydrostatic, primitive-equation ocean model, this study investigates the dynamics of lateral circulation in a partially stratified tidal inlet, the Barataria Pass in the Gulf of Mexico, over a 25.6 h diurnal tidal cycle. Mo...
Accurate prediction of key environmental parameters is crucial for intelligent control and optimization, yet it remains challenging due to gradient instability in deep learning models, like Long Short-Term Memory (LSTM), during time series forecastin...
The zero-inflated Bernoulli model, enhanced with elastic net regularization, effectively handles binary classification for zero-inflated datasets. This zero-inflated structure significantly contributes to data imbalance. To improve the ZIBer model&rs...
The implementation of accurate water balance assessment in glacier basins is essential for the management and sustainable development of water resources in the basins. In this study, a hybrid modeling framework was constructed to enhance runoff predi...
This study presents the first longitudinal measurement of the intracellular/extracellular pH gradient in a rat glioma model using noninvasive magnetic resonance imaging. The acid–base balance in the brain is tightly controlled by endogenous buffers....
The study compares model approaches in predictive modeling for claim frequency and severity within the cross-border cargo insurance domain. The aim is to identify the optimal model approach between generalized linear models (GLMs) and advanced machin...
The state of charge (SOC) plays a critical role in battery management systems. This paper discusses the stability of the nonlinear SOC observer based on the extended Kalman filter. The model characterizing the lithium-ion battery nonlinearity is the...
The mathematical nature of the flow rule for the strain gradient plasticity theory proposed by Nix and Gao (W.D. Nix and H. Gao, J Mech Phys Solids 46(3), 411(1998)) is discussed based on the paradigm developed by Gurtin and Anand (M.E. Gurtin and L....
Although the theory of ecosystem services (ESs) is important for guiding land-use planning, knowledge of ESs trade-offs and supply–demand mechanisms is still lacking, and the characteristics of the correlation between the size of trade-offs and...
The simplest model for an atmospheric boundary layer assumes a uniform steady wind over a certain depth, of order 1 km, with the forces of friction, pressure gradient and Coriolis in balance. A linear model is here employed for the adjustment of wind...
Water resources provided by alpine glaciers are an important pillar for people in the arid regions of west China. In this study, the Hydrologiska Byrans Vattenavdelning (HBV) light model was applied to simulate glacier mass balance (GMB) and runoff i...
Large-truck crashes often result in substantial economic and social costs. Accurate prediction of the severity level of a reported truck crash can help rescue teams and emergency medical services take the right actions and provide proper medical care...
Despite their high prediction accuracy, deep learning-based soft sensor (DLSS) models face challenges related to adversarial robustness against malicious adversarial attacks, which hinder their widespread deployment and safe application. Although adv...
Heating systems in a building’s mechanical infrastructure account for a significant share of global building energy consumption, underscoring the need for improved efficiency. This study evaluates 31 predictive models—including neural net...
Mass balance of glaciers in High Mountain Asia (HMA) varies substantially across the region. While the spatial variability is attributed to differences in climatic setting and sensitivity of these glaciers to climate change, an assessment of these fa...
This paper introduces an enhanced variant of the Adam optimizer—the BGE-Adam optimization algorithm—that integrates three innovative technologies to augment the adaptability, convergence, and robustness of the original algorithm under var...
Spherical parallel robots (SPR) are widely used in industries and robotic rehabilitation. Designing such systems for better balance properties is still a challenge. This paper presents a work to minimize the shaking moment for a fully force-balanced...
The purpose of this work is to develop a model for balancing the processes of the generation and consumption of electricity, taking into account the random nature of these processes. The subject of the study is hybrid power systems that use tradition...
This study analyzes the key factors influencing player rank prediction in PlayerUnknown’s Battlegrounds (PUBG), using machine learning models to evaluate in-game performance. By examining variables such as “walkDistance”, “boo...
Multi-beam satellite communication systems are promising architectures in the future. A packet is transmitted by multi-satellite and multi-beam cooperatively, which can provide efficient spectrum utilization, improve system throughput, and guarantee...
Phishing leverages people’s tendency to share personal information online. Phishing attacks often begin with an email and can be used for a variety of purposes. The cybercriminal will employ social engineering techniques to get the target to cl...
Hearing loss significantly impacts daily communication, making accurate speech audiometry (SA) assessment essential for diagnosis and treatment. However, SA testing is time-consuming and resource-intensive, limiting its accessibility in clinical prac...
In this paper, we propose a non-convex model with fractional-order applied to image deblurring problems. In the new model, fractional-order gradients have been introduced to preserve detailed features, and a source term with a blurry kernel is used f...
Deep learning technology has advanced rapidly and has started to be applied for the detection of welding defects. In the manufacturing process of power batteries for new energy vehicles, welding defects may occur due to the high directivity, converge...
Wireless traffic prediction is critical to the intelligent operation of cellular networks, such as load balancing, congestion control, value-added service promotion, etc. However, the BTS data in each region has certain differences and privacy, and c...
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable Artificial Intelligence (XAI) models for data imputations and numerical or categorical hydroclimatic predictions from nonlinearly combined multidimensional...
Geodetic mass changes in the Svalbard glaciers Austre Lovénbreen and Pedersenbreen were studied via high-precision real-time kinematic (RTK)-global positioning system (GPS) measurements from 2013 to 2015. To evaluate the elevation changes of t...
This paper presents a proposed LSTM-based vertical-gradient prediction combined with three-dimensional kriging that enables reconstruction of greenhouse 3D temperature fields under sparse-sensor deployments while capturing temporal dynamics and spati...
Accurate prediction of bridge deterioration is essential for optimizing inspection schedules, prioritizing maintenance activities, and ensuring infrastructure safety. This study developed machine learning-based predictive models to estimate the deter...
Purpose: To develop and validate machine learning models for predicting the length of stay (LOS) in the Pediatric Intensive Care Unit (PICU) using data from the Virtual Pediatric Systems (VPS) database. Methods: A retrospective study was conducted ut...
Federated learning (FL) enables collaborative model training across multiple institutions without the sharing of raw patient data, making it particularly suitable for smart healthcare applications. However, recent studies revealed that merely sharing...
High dropout rates remain a significant challenge in Massive Open Online Courses (MOOCs), making early identification of at-risk students crucial. This study introduces a novel approach called In-Session Stacked Ensemble Learning for Dropout Predicti...
Wildfires directly threaten the safety of life and property. Predicting wildfires with a model driven by wildfire danger factors can significantly reduce losses. Weather conditions continuously influence the drying rate of fuel as well as the occurre...
The banking industry faces significant challenges, from high customer churn rates to threatening long-term revenue generation. Traditionally, churn models assess service quality using customer satisfaction metrics; however, these subjective variables...
Annual mass balance is an important reflection of glacier status that is also very sensitive to climate fluctuations. However, there is no effective and universal albedo-based method for the reconstruction of annual mass balance due to the scarcity o...
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