Residual Method Research Articles

Advancing thermal efficiency and entropy management inside decagonal enclosure with and without hot cylindrical insertions

Effective cooling mechanisms are considered advancements in thermal control systems for diverse engineering purposes. Considering this fact, this investigation explores the analysis of natural convection and entropy generation by employing a decagonal enclosure using Galerkin Residual Finite Element method. In this study, influence of Rayleigh number (103 ≤ Ra ≤ 106), Bejan number (Be), Prandtl number (0.71 ≤ Pr ≤ 7), and isothermal boundary condition are considered. The findings reveal that both Ra and Pr significantly impact the characteristics of convection and flow patterns within the system. In cases with and without the circular object, higher values of Pr and Ra lead to a more pronounced cooling effect on the upper heated surface compared to the lower surface. Also, it enhances the overall thermal efficiency of the system by 112.05 % in comparison to the absence of a cylinder enclosure. These findings shed light on thermal control system advancements and contribute to field progress.

Three-dimensional slope stability analysis based on irregular ellipsoid sliding surface

The determination of the critical sliding surface is a crucial aspect of slope stability analysis. In reality, the environment in which slopes are located is often very complex, and the sliding surfaces have different shapes. Therefore, a three-dimensional stability study is proposed, using irregular ellipsoidal shapes as the sliding surface. By constructing the equation of the irregular ellipsoid and applying spatial geometric transformations, an irregular ellipsoid controlled by six parameters, (semi-axis length (a), width (b), height (c), rotation angle (θ), and spatial displacements (tx and tz)), is obtained. The interpolation method is employed to apply the irregular ellipsoid to 3D slopes, thereby generating irregular ellipsoidal sliding surfaces. The slope stability coefficient is calculated by using the residual thrust method and genetic algorithm to determine the critical sliding surface. A comparative stability analysis is conducted between the standard ellipsoidal sliding surface and the irregular ellipsoidal sliding surface through a classic case study. The results show that the Type II irregular ellipsoidal sliding surface aligns well with the mining area. Finally, the research findings are applied to the 3D slope stability analysis of the Shengli West No.2 Open-Pit Coal Mine in China, validating the feasibility of the proposed method.

A Residual Selectable Modeling Method Based on Deep Neural Network for Power Amplifiers With Multiple States

A Residual Selectable Modeling Method Based on Deep Neural Network for Power Amplifiers With Multiple States

Minimum residual shift-splitting iteration method for non-Hermitian positive definite and positive semidefinite linear systems

By applying the minimum residual technique to the shift-splitting (SS) iteration scheme, we introduce a non-stationary iteration method named minimum residual SS (MRSS) iteration method to solve non-Hermitian positive definite and positive semidefinite systems of linear equations. Theoretical analyses show that the MRSS iteration method is unconditionally convergent for both of the two kinds of systems of linear equations. Numerical examples are employed to verify the feasibility and effectiveness of the MRSS iteration method.

Dynamic weighted residual ensemble learning for hyperspectral image classification driven by features and samples

Dynamic ensemble selection has emerged as a promising approach for hyperspectral image classification. However, selecting relevant features and informative samples remains a pressing challenge. To address this issue, we introduce two novel dynamic residual ensemble learning methods. The first proposed method is called multi-features driven dynamic weighted residuals ensemble learning (MF-DWRL). This method leverages various combinations of features to construct classifier pools that incorporate feature differences. The K-Nearest Neighbors algorithm is employed to establish the region of competence (RoC) in the dynamic ensemble selection process. By assessing the performance of the RoC, the feature sets that yield the highest classification accuracy are identified as the optimal feature combinations. Additionally, the classification accuracy is utilized as prior information to guide the residual adjustments of each classifier. The second method, known as features and samples double-driven dynamic weighted residual ensemble learning (FS-DWRL), further enhances the performance of the ensemble. This approach not only considers the selection of feature combinations but also takes into account the informative samples. By jointly optimizing the feature and sample selection processes, FS-DWRL achieves superior classification accuracy compared to existing state-of-the-art methods. To evaluate the effectiveness of the proposed methods, three hyperspectral datasets from China—WHU-Hi-HanChuan, WHU-Hi-LongKou, and WHU-Hi-HongHu—are used for classification experiments. For these datasets, the proposed methods achieve the highest classification accuracies of 90.57 %, 98.77 %, and 91.08 %, respectively. The MF-DWRL and FS-DWRL methods exhibit significant improvements in classification accuracy.

UG secondary development of path generation of straight profile toroidal worm finishing tool

Abstract Due to the complexity of the right and left tooth surfaces of the straight profile toroidal worm, it is difficult in 3D modeling and NC programming. Based on the equal residual height algorithm, this paper deduces the calculation formula of the cutter contact and cutter point of the tooth surface of the straight profile toroidal worm by using the round nose milling cutter, calculates the cutter point coordinates and rotation angles of each point of the tooth surface of the straight profile toroidal worm through the UG secondary development interface and Visual Studio software, and generates the numerical control code on this basis. The machining simulation and experiment show that the machining efficiency and error of the straight profile torus worm machined by the tool path prepared by the equal residual height method are better than that of the isoparametric method.

Generative adversarial network for Multimodal Contrastive Domain Sharing based on efficient invariant feature-centric growth analysis improved brain tumor classification

ABSTRACT Efficient and accurate classification of brain tumor categories remains a critical challenge in medical imaging. While existing techniques have made strides, their reliance on generic features often leads to suboptimal results. To overcome these issues, Multimodal Contrastive Domain Sharing Generative Adversarial Network for Improved Brain Tumor Classification Based on Efficient Invariant Feature Centric Growth Analysis (MCDS-GNN-IBTC-CGA) is proposed in this manuscript.Here, the input imagesare amassed from brain tumor dataset. Then the input images are preprocesssed using Range – Doppler Matched Filter (RDMF) for improving the quality of the image. Then Ternary Pattern and Discrete Wavelet Transforms (TPDWT) is employed for feature extraction and focusing on white, gray mass, edge correlation, and depth features. The proposed method leverages Multimodal Contrastive Domain Sharing Generative Adversarial Network (MCDS-GNN) to categorize brain tumor images into Glioma, Meningioma, and Pituitary tumors. Finally, Coati Optimization Algorithm (COA) optimizes MCDS-GNN’s weight parameters. The proposed MCDS-GNN-IBTC-CGA is empirically evaluated utilizing accuracy, specificity, sensitivity, Precision, F1-score,Mean Square Error (MSE). Here, MCDS-GNN-IBTC-CGA attains 12.75%, 11.39%, 13.35%, 11.42% and 12.98% greater accuracy comparing to the existingstate-of-the-arts techniques, likeMRI brain tumor categorization utilizing parallel deep convolutional neural networks (PDCNN-BTC), attention-guided convolutional neural network for the categorization of braintumor (AGCNN-BTC), intelligent driven deep residual learning method for the categorization of braintumor (DCRN-BTC),fully convolutional neural networks method for the classification of braintumor (FCNN-BTC), Convolutional Neural Network and Multi-Layer Perceptron based brain tumor classification (CNN-MLP-BTC) respectively.

Thermal criticality and two-step diffusion-reaction of electromagnetic Casson-Williamson fluid flow along a vertical channel with convective cooling under bimolecular kinetic

The need to examine diverse conditions involving industrial working fluids and improving thermal transfer efficiency cannot be overstated. Every thermal system must monitor and control excessive heat production and propagation to avert disruptions in various engineering processes. Therefore, the study investigated the theoretical significance of thermal criticality and a two-step exothermic reaction on Casson-Williamson fluid dynamics behaviour through a fixed vertical channel driven by an electromagnetic field, axial pressure gradient, and heat buoyancy force under a generalized bimolecular chemical kinetic. The heat exchange at the convective wall surface is adhered to Newton’s law of cooling. The Galerkin weighted residual method (GWRM) was utilized to solve the dimensionless nonlinear equations governing the flow within the boundary layer, yielding graphical representations of momentum and energy distributions. The results show that higher values of the activation energy, Frank-Kamenetskii parameter, electric field loading, activation ratio term, Weissenberg number, and second step term led to better heat dispersion and, eventually, complete combustion of hydrocarbons in the Casson-Williamson fluid. To avoid system disruptions, the study underscores the crucial need for continuous monitoring of all factors that stimulate internal heat generation to prevent system failures, emphasizing the importance of vigilance in the field of thermal systems.

Analytical Treatment for Solving Fourth Order of Fuzzy Boundary Value Problems Using Residual Power Series Method

Analytical Treatment for Solving Fourth Order of Fuzzy Boundary Value Problems Using Residual Power Series Method

Causal relationship between systemic lupus erythematosus and adverse pregnancy outcomes: A two-sample Mendelian randomized study

BackgroundSystemic lupus erythematosus (SLE) is associated with adverse pregnancy outcome (APO). However, the genetic causality of this association remains unclear. In this study, Mendelian randomization (MR) was used to explore the potential causal relationship between SLE and APO risk. MethodsWe selected 45 single nucleotide polymorphisms (SNPs) associated with SLE from published genome-wide association studies (GWAS). APO's statistics are obtained from the GWAS database. MR estimates were performed using the inverse variance-weighted (IVW) method, the MR-Egger method, and the weighted median (WM) method. Sensitivity analysis was performed using Cochran's Q test, MR-Egger intercept, MR-pleiotropic residual and outlier method, stay-one analysis and funnel plot. ResultsThe results showed a causal relationship between SLE and pre-eclampsia (OR = 1.036, 95 % confidence interval 1.006 to 1.068, P = 0.019), and no significant causal relationship was found between SLE and other adverse pregnancy outcomes, including postpartum hemorrhage, placental abruption, spontaneous abortion, premature rupture of membranes, fetal distress, gestational diabetes mellitus. These findings were robust in several sensitivity analyses. ConclusionThis MR study demonstrated the causal effect of SLE on preeclampsia. It provides important clues for identifying and early predicting risk factors for preeclampsia.

Tiny particles thermal motile in magnetized chemically reacting upper-convective Maxwell stagnation point fluid with radiation

The need to enhance industrial working fluid and material thermal strength for quality output of engineering and domestic devices, has increased diverse studies on non-Newtonian viscous fluid under different constraints. Various architectures and geometries have been considered for thermal propagation of fluid particles. As such, this study addresses thermal motility of tiny particles in magnetized chemically reacting upper-convective Maxwell stagnation point fluid with radiation owing to its usages. A partial-differential model is formulated under some certain assumptions and conditions, and with applicable similarity variables, a transformed invariant coupled ordinary-differential model is obtained. The solutions to the model are determined using Galerkin-weighted residual method. The computed outcomes are quantitatively tabulated and qualitatively demonstrated in graphs. The analysis revealed that the hydrodynamic bounding surface alongside with velocity profiles declines due to augmentation of the magnetic field and Deborah number terms.

Adaptive time-domain impact extraction method for multi-source impact vibration signal of diesel engine

Diesel engines are widely used in fields such as ships, vehicles, and nuclear power. The vibration signals of a diesel engine’s casing exhibit a characteristic of intermittent distribution of multi-source impacts. In response to the challenges faced by existing feature extraction methods in identifying and localizing impact signals, this paper proposes the adaptive time-domain impact extraction (ATDIE) method, which is based on the characteristics of impact signals exhibiting local high-energy distribution in the time domain and rapid amplitude decay. The purpose of the ATDIE method is to extract various impact components from multi-source impact signals. The ATDIE method constructs a solution model with the goal of minimizing the signal’s multi-order amplitude central moments. By using the residual iterative solution method, the number of extracted components is adaptively determined. Then, an impact window optimization function is established to enhance the adaptability. Finally, the test results with both simulation signals and diesel engine signals demonstrate that the ATDIE method possesses good capabilities for impact extraction and computational efficiency.

Numerical Analysis of a Time-Simultaneous Multigrid Solver for Stabilized Convection-Dominated Transport Problems in 1D

This work focuses on the solution of the convection–diffusion equation, especially for small diffusion coefficients, employing a time-simultaneous multigrid algorithm, which is closely related to multigrid waveform relaxation. For discretization purposes, linear finite elements are used while the Crank–Nicolson scheme acts as the time integrator. By combining all time steps into a global linear system of equations and rearranging the degrees of freedom, a space-only problem is formed with vector-valued unknowns for each spatial node. The generalized minimal residual method with block Jacobi preconditioning can be used to numerically solve the (spatial) problem, allowing a higher degree of parallelization in space. A time-simultaneous multigrid approach is applied, utilizing space-only coarsening and the aforementioned solution techniques for smoothing purposes. Numerical studies analyze the iterative solution technique for 1D test problems. For the heat equation, the number of iterations stays bounded independently of the number of time steps, the time increment, and the spatial resolution. However, convergence issues arise in situations where the diffusion coefficient is small compared to the grid size and the magnitude of the velocity field. Therefore, a higher-order variational multiscale stabilization is used to improve the convergence behavior and solution smoothness without compromising its accuracy in convection-dominated scenarios.

Excess goodwill and enterprise litigation risk

Corporate mergers and acquisitions (M&A) are now a common strategic choice for enterprises. As such, goodwill, which is a core asset of M&A activities, is pivotal for financial valuation and accounting. However, the phenomenon of ‘excess goodwill’, resulting from overvaluation due to management overconfidence and performance promises, poses significant risks, including potential financial statement distortions and increased litigation. This study investigates the intrinsic link between excess goodwill and corporate litigation risk by utilising theoretical analyses and empirical tests. By analysing data from A-share listed companies in Shanghai and Shenzhen from 2007 to 2022, we employed the regression residual method to measure excess goodwill and determine its impact on litigation risk through mediating factors such as financing constraints, risk-taking and agency costs. The findings indicate that excess goodwill significantly increases litigation risk, with a more pronounced effect on manufacturing firms and those with low internal control quality. This research provides valuable insights into optimising goodwill accounting treatment and enhancing enterprise risk management practices. The study's implications suggest that stricter internal controls and cautious goodwill valuation practices are essential to mitigate risks, ultimately contributing to the stability of the capital market and the protection of investor interests.

Fast and economic method for chlorpropham residues screening in potato peel

Chlorpropham is a selective and systemic herbicide extensively used to control sprouting, a major process affecting the quality of stored potatoes. Main concern about the usage of chlorpropham arises from the fact that chlorpropham degrades to toxic aniline-based metabolites during thermal processing of potatoes. The issue has led to chlorpropham withdrawal from the treatment practices, however, cross contamination from storage facilities requires ongoing monitoring of pesticide residues for a prolonged period. This study offers a fast and economic method suitable for chlorpropham screening in potatoes. The developed method targets the potato peel, simply prepared and analyzed by GC/MS. The method performance and cost-effectiveness were compared to that of the official method for chlorpropham analysis approved by the European Food Safety Authority. The method was used for the targeted analysis of potato samples from southeastern Serbia.

Chemical composition of muscle tissue of fish reared in the aquaculture of South Vietnam

To study the chemical composition of four species of valuable fish reared in aquaculture conditions in South Vietnam.Individuals of Channa striata, Channa gachua, Oreochromis niloticus, a hybrid of Clarias gariepinus and Clarias macrocephalus were purchased in markets from farmers of cage farms and directly in the farms of Khanh Hoa province. The fish were measured, weighed, and then muscle tissue was dissected for chemical analysis. The water content in the tissue was determined by a two‐stage method for determining moisture, while lipids were determined by the fat‐free residue method in a Soxhlet apparatus. The amount of protein was obtained according to the principle of the Kjeldahl method, using a semi‐automatic distillation unit UDK 139 (Velp Scientifica, Italy, 2011); minerals were determined by the gravimetric method, and carbohydrates – by calculation. The index of physiological state was calculated according to the standard method.Hybrid catfish muscles are characterised as having the greatest nutritional value. In terms of lipid content, the individuals studied belonged to fish with a low fat content, Channa striata, which belongs to the category of lean fish. A high index of physiological state in Oreochromis niloticus was found to be associated with increased water content in muscle tissue. No significant differences were found between the biochemical parameters in the muscles of fish with an increase in body size, and only in Channa striata did the proportion of minerals increase. The data obtained can be used in the organisation of rational feeding and maintenance of aquacultural species.

Transient Friction Analysis of Pressure Waves Propagating in Power-Law Non-Newtonian Fluids

Modulated pressure waves propagating in the drilling fluids inside the drill string are a reliable real-time communication technology that transmit data from downhole to the surface during oil and gas drilling. In the analysis of pressure waves’ propagation characteristics, the modeling of transient friction in non-Newtonian fluids remains a great challenge. This paper establishes a numerical model for transient pipe flow of power-law non-Newtonian fluids by using the weighted residual collocation method. Then, the Newton–Raphson method is applied to solve the nonlinear equations. The numerical method is validated by using the theoretical solution of Newtonian fluids and is proven to converge reliably with larger time steps. Finally, the influencing factors of the wall shear stress are analyzed using this numerical method. For shear-thinning fluids, the friction loss of periodic flow decreases with the increase in flow rate, which is opposite to the variation law of friction with the flow rate for stable pipe flow. Keeping the amplitude of pressure pulsation unchanged, an increase in frequency leads to a decrease in velocity fluctuations; therefore, the friction loss decreases with the increase in frequency.

Analysis of electromagnetic and radiative heat source on tangential hyperbolic fluid under Arrhenius kinetic with convective cooling

The global threat of environmental degradation from harmful waste discharge is evident, leading to unusual diseases and natural disasters. Some of these toxic emissions result from human activities, such as the incomplete combustion of hydrocarbons. As such, this study aims to explore the analysis of electromagnetic and radiative heat sources on tangential hyperbolic fluid under Arrhenius kinetic with convective cooling. The transformed momentum and heat equations are solved using a rigorous computational approach called the Galerkin integration approximation with weighted residual method. This computational methodology ensures the reliability and accuracy of the results. Various graphs illustrate the results, showing parametric sensitivity profiles for the velocity, temperature, skin friction, thermal gradient, Bejan, and entropy generation. As noticed from the outcomes, electric field loading increases heat dispersion by about 3.25 % as heat source terms are enhanced. Increasing magnetic field, radiation, and electric field loading parameters strengthened thermodynamic equilibrium and minimized entropy generation. The tangential hyperbolic combustion process is 6.11 % increased with rising Brinkman number and electric field loading terms. The flow rate and temperature field are increased to the peak along the middle of the channel for increasing pressure gradient.

Employing the Laplace Residual Power Series Method to Solve (1+1)- and (2+1)-Dimensional Time-Fractional Nonlinear Differential Equations

Employing the Laplace Residual Power Series Method to Solve (1+1)- and (2+1)-Dimensional Time-Fractional Nonlinear Differential Equations

Parameter estimation of uncertain stock model using residual method optimized by genetic algorithm: valuation of vulnerable European and barrier options

Parameter estimation of uncertain stock model using residual method optimized by genetic algorithm: valuation of vulnerable European and barrier options