The Adam algorithm is a widely used optimizer for neural network training due to efficient convergence speed. The algorithm is prone to unstable learning rate and performance degradation on some models. To solve these problems, in this paper, an impr...
Background and Objectives: Cardiovascular and cerebrovascular diseases caused by arterial stenosis and sclerosis are the main causes of human death. Although there are mature diagnostic techniques in clinical practice, they are not suitable for early...
A comprehensive linear gradient solvent system for centrifugal partition chromatography (CPC) was developed for the bioassay-guided isolation of natural compounds. The gradient solvent system consisted of three different ternary biphasic solvents typ...
The practical application of flexible pressure sensors, including electronic skins, wearable devices, human–machine interaction, etc., has attracted widespread attention. However, the linear response range of pressure sensors remains an issue....
Multi-buoy sonar systems achieve target localization by receiving broadband Linear Frequency Modulation signals emitted from the transmitter. Accurate estimations of the parameters of Linear Frequency Modulation signals significantly enhance the loca...
Bilevel optimization is a fundamental framework for hierarchical decision-making, but its solution is challenging due to the implicit and typically set-valued nature of the lower-level optimality condition. In this paper, we study bilevel optimizatio...
To solve the
Drought is a slow-onset hazard whose economic impacts can propagate across sectors with multi-year delays. This study develops a non-linear autoregressive model with exogenous drought inputs (ARX) to assess whether U.S. drought severity, measured by...
Toddalia asiatica (L.) Lam. (Rutaceae) has shown a broad spectrum of biological properties, such as anti-inflammatory, antioxidant, antimicrobial, anti-HIV, and anticancer properties. The present study is concerned with the separation of the main com...
Powered parafoils, known for their impressive load-bearing capacity and extended endurance, have garnered significant interest. However, the parafoil system is a highly complex nonlinear system. It primarily relies on the steering gear to change flig...
This paper presents the design, development, and evaluation of a machine-learning system built to forecast agricultural crop yields across Indian states between 2000 and 2026, together with a complementary, national-scale verification of predicted cr...
The existing literature predominantly concentrates on the utilization of the gradient descent algorithm for control systems’ design in power systems for stability enhancement. In this paper, various flavors of the Conjugate Gradient (CG) algorithm ha...
We consider the existence and uniqueness of the saturated classical solutions and the positive classical solutions to initial boundary value problems of semi-linear sub-diffusion with gradient terms. Applying this to the fractional power of the secto...
In this paper, a two-point step-size gradient technique is proposed by which the approximate solutions of a non-linear system are found. The two-point step-size includes two types of parameters deterministic and random. A new adaptive backtracking li...
We are focusing on the algorithms for solving the large-scale convex optimization problem in linear elasticity contact problems discretized by Finite Element method (FEM). The unknowns of the problem are the displacements of the FEM nodes, the corres...
Thousands of vessels travel around the world every day, making the safety, efficiency, and optimization of marine transportation essential. Therefore, the knowledge of bathymetry is crucial for a variety of maritime applications, such as shipping and...
In the wave of digital transformation and Industry 4.0, accurate time series forecasting has become critical across industries such as manufacturing, energy, and finance. However, while deep learning models offer high predictive accuracy, their lack...
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...
A numerical scheme is said to be locally exact if after linearization (around any point) it becomes exact. In this paper, we begin with a short review on exact and locally exact integrators for ordinary differential equations. Then, we extend our app...
In this paper, we propose the simultaneous sub-gradient projection algorithm with the dynamic step size (SSPA for short) for solving the multiple-sets split feasibility problem (MSSFP for short) and investigate its linear convergence. We involve a no...
Due to the complexity and illegibility of medical images, it brings inconvenience and difficulty to the diagnosis of medical personnel. To address these issues, an optimization algorithm called GSL(Gradient sine linear) based on Adam algorithm improv...
Due to the time delay and some unavoidable noise factors, obtaining a real-time solution of dynamic time-varying linear matrix equation (LME) problems is of great importance in the scientific and engineering fields. In this paper, based on the philos...
Active waveguide Bragg gratings (AWBGs) combine the narrowband reflectivity of Bragg gratings with the optical gain of rare-earth-doped media, representing a versatile platform for monolithic lasers and amplifying reflectors. The lasing regime in the...
Modern machine learning methods, such as tree ensembles, have recently become extremely popular due to their versatility and scalability in handling heterogeneous data and have been successfully applied across a wide range of domains. In this study,...
As a special class of non-negative matrix factorization, symmetric non-negative matrix factorization (SymNMF) has been widely used in the machine learning field to mine the hidden non-linear structure of data. Due to the non-negative constraint and n...
Optimal tracking control aims to steer a dynamical system along a desired reference trajectory while minimizing a prescribed performance cost. This problem becomes substantially more difficult when both the controlled system dynamics and the target d...
This study presents a wide-linear-range flexible pressure sensor based on a gradient non-uniform porous structure. Through co-optimization of material composition and structural parameters, the sensor integrates high sensitivity, a broad linear respo...
Climate change is one of the most pressing global challenges that could potentially threaten ecosystems, human populations, and weather patterns over time. Impacts including rising sea levels and soil salinization are caused by climate change, primar...
Various offset-free economic model predictive control schemes that include a disturbance model and the modifier-adaptation principle have been proposed in recent years. These schemes are able to reach plant optimality asymptotically even in the prese...
The spontaneous oscillations within the brain are intimately linked to the hierarchical structures of the cortex, as evidenced by the cross-cortical gradient between parametrized spontaneous oscillations and cortical locations. Despite the significan...
Large-scale symmetric and asymmetric matrices have emerged in predicting the relationship between genes and diseases. The emergence of large-scale matrices increases the computational complexity of the problem. Therefore, using low-rank matrices inst...
In distributed optimization, communication bottlenecks and computational heterogeneity are two critical challenges that undermine system scalability and efficiency. To address these issues, we propose a synchronous algorithm, CC-GT (Conjugate Compres...
In automotive millimeter-wave (MMW) radar systems, achieving high-precision direction of arrival (DOA) estimation with a limited number of array elements is a crucial research focus. Compressive sensing (CS) techniques have been demonstrated to offer...
In the modern age, watermarking techniques are mandatory to secure digital communication over the internet. For an optimal technique, a high signal-to-noise ratio and normalized correctional is required. In this paper, a digital watermarking techniqu...
This paper focuses on an important issue regarding the forecasting of the hourly energy consumption in the case of large electricity non-household consumers that account for a significant percentage of the whole electricity consumption, the accurate...
In this paper, a gradient descent algorithm is proposed for the parameter estimation of multi-input and multi-output (MIMO) total non-linear dynamic models. Firstly, the MIMO total non-linear model is mapped to a non-completely connected feedforward...
In this paper, we study the nonconvex quadratic programming over the intersection of two balls in n-dimensional complex space, which is called the uniform CDT subproblem and is significant in both optimization theory and applications. We first prove...
This study introduces a novel mathematical framework for a machine learning algorithm tailored to address linear regression problems in the presence of non-Gaussian estimation noise. In particular, we focus on Bernoulli–Gaussian noise, which fr...
This study introduces a fragmentation-based linear-scaling method for strongly correlated systems, specifically the divide-and-conquer Hartree–Fock–Bogoliubov (DC-HFB) approach. Two energy gradient formulations of the DC-HFB method are de...
Coal-mining subsidence lakes are an expanding artificial wetland type in China, yet the relationships between waterbird diversity components and water-quality and landscape gradients remain unclear. We conducted monthly point-count surveys from Janua...
In this research, an intelligent control architecture for an experimental Unmanned Aerial Vehicle (UAV) bearing unconventional inverted V-tail design, is presented. To handle UAV’s inherent control complexities, while keeping them computational...
The Lagrangian meshfree particle-based method has advantages in solving fluid dynamics problems with complex or time-evolving boundaries for a single phase or multiple phases. A pure Lagrangian meshfree particle method based on a generalized finite d...
In this paper, we propose a new finite-difference method for nonconvex absolute value equations. The nonsmooth unconstrained optimization problem equivalent to the absolute value equations is considered. The finite-difference technique is considered...
This paper discusses an adaptive method of image steganography issues based on the application of a linear hash function over the GF (2) field to control the embedding process. The method uses staggered splitting of an image into 8 × 8-pixel bl...
In traditional Stripmap SAR imaging, the platform motion error will bring the phase error in the azimuthal direction to the image, which will have a series of effects on the imaging quality. The traditional autofocus algorithm—Stripmap Phase Gr...
Remotely operated vehicles (ROVs) face challenges in achieving optimal trajectory tracking performance during underwater movement due to external disturbances and parameter uncertainties. To address this issue, this paper proposes a position and atti...
The current research has aimed to investigate and develop machine-learning approaches by using the data in the dataset to be applied to classify location-based social network data and predict user activities based on the nature of various locations (...
In the field of video image processing, high definition is one of the main directions for future development. Faced with the curse of dimensionality caused by the increasingly large amount of ultra-high-definition video data, effective dimensionality...
The proposal of local differential privacy solves the problem that the data collector must be trusted in centralized differential privacy models. The statistical analysis of numerical data under local differential privacy has been widely studied by m...
This study introduces a novel deposition technique capable of depositing thin films with any arbitrary thickness profile. The apparatus consists of a fixed shadow mask and a rotating sample carrier plate. The shadow mask features a specifically desig...
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