Local Method Research Articles

An Improved P-wave Peak Location Method Based on Pan-Tompkins Algorithm

Electrocardiogram (ECG) signal can reflect the health of the heart, and P wave is an important part of ECG signal, which reflects the excitatory conduction process of the heart. By precisely locating the P waves in the ECG signal, important information about heart disease can be obtained. In this paper, a method of P-wave peak localization based on Pan-Tompkins algorithm is proposed. Firstly, the ECG signal is decomposed by wavelet transform, and the coefficients of each layer are processed to filter out the noise such as baseline drift and electromyographic interference in the ECG signal. After the location of R wave in the signal was found by the Pan-Tompkins algorithm, the QRS wave was eliminated, and then the possible P wave location was found by the improved Pan-Tompkins algorithm. Finally, the correct P wave was screened by a screening strategy. Experimental results show that the sensitivity and accuracy of the P-wave localization algorithm proposed in this paper reach 94.78% and 95.10%, respectively. It shows that the proposed algorithm has good performance for P-wave localization.

Numerical study of shock wave boundary layer interaction flows using a novel turbulence model

This study proposes a novel partial average fluctuation velocity (PAFV) turbulence based on the PAFV and the average strain rate tensor, which is used to calculate the shock wave boundary layer interaction flows, including cascade flow and transonic compressor flow. In order to illustrate the adequacy, the calculation results of several other turbulence models were also compared with PAFV, including k-ω, shear stress transport, SA-neg (negative Spalart-Allmaras), and stress-BSL (ω-based Reynolds stress model). The suitability of the PAFV turbulence model was initially tested by calculating the transonic flow in the L030-4 cascade. Subsequently, numerical computations were performed for the 3D (three-dimensional) National Aeronautics and Space Administration Rotor 67 transonic compressor rotor. In the numerical simulation, the flow control equations were transformed in a general curvilinear coordinate system for precision enhancement, and the spatial discretization of control equations was executed using the finite difference method. The convection term was processed using the Steger–Warming flux vector splitting method, the diffusion term was discretized using a second-order central difference scheme, and the time derivative term was discretized using the third-order Runge–Kutta method. A parallel computing strategy with multi-block partitioning was employed to speed up the calculations and facilitate faster convergence alongside a local time step method. All numerical computation procedures were written in Python, revealing the following: (1) The PAFV turbulence model aptly simulates the transonic flow within the cascade channel. The shock wave pattern in the cascade channel aligns well with the experimental schlieren images. (2) During the Rotor 67 transonic compressor rotor calculation, the flow–pressure ratio, flow efficiency, and inlet and outlet total temperatures and pressures align well with the experimental data. Furthermore, the resolution of the flow field structure related to the interaction between the tip leakage vortex and channel shock wave is high. (3) The turbulence model uses PAFV as the turbulence velocity scale, thereby suppressing the fluctuation velocity and turbulence viscosity near shock wave areas, preventing excessive turbulence viscosity. Moreover, PAFV inherently exhibits transport properties and anisotropic characteristics, making it well-suited for handling transonic compressor flows.

Fourth-order phase-field simulation of cracks using strong form meshless method

The prediction of crack propagation in fracture mechanics is still a fundamental challenge. In recent decades, phase-field formulation emerged as a powerful tool for the simulation of crack evolution, which offers a continuous representation of cracks from intact to broken material. For the first time, the present study combines a fourth-order phase field and a strong-form meshless method to investigate crack propagation in brittle elastic material. The local radial basis function collocation method, structured with the augmented polyharmonic splines, is used to solve the coupled mechanical and phase-field models. Due to the smooth nature of the fourth-order phase-field model, the sharp transition at the crack surface can be avoided. It is found that the presented method successfully predicts the crack propagation for a material subjected to tensile loading. The obtained results agree well with the benchmark case. Further study will include elastoplastic material behaviour and applications to crack formation in different steel processing steps.

A Systematic Review of Loco-Sedative Anesthesia for Urologic Surgery

ObjectiveTo perform a systematic review of the characteristics and outcomes of conscious sedation and local anesthesia for various urologic procedures. Urologic care has much to gain from the routine integration of ambulatory surgery via loco-sedative anesthetic techniques for both surgeon and patient. MethodsA comprehensive systematic literature search was conducted on PubMed, and Scopus databases following PRISMA criteria from June to August 2021. Articles were included if they were English, prospective, randomized, or non-randomized controlled trials that used local anesthetic or conscious sedation for urologic interventions in adult patients. Additionally, included studies provided primary data on the use loco-sedative anesthesia and the efficacy and complications. All studies included were further reviewed to assess the biases and conflicts of interests. Results32 studies with 6897 patients were included in the review. Mean patient age was 46.4 years. The most common anesthetic and analgesic relief was the use of local anesthetic with 1% lidocaine. The majority used lidocaine as an injection, whereas the second most common route of administration was a topical cream. However, there was significant heterogeneity in the type of local or conscious sedation method and whether a combination was used. 44.4% of the studies used the visual analog scale as their primary endpoint. All the studies reported an 83% to 100% successful procedure rate without note of significant sedation-related complications. ConclusionsGiven the high efficacy rates, loco-sedative anesthesia is a promising technique for urologic interventions and should be further investigated to determine whether it may become be the standard of care.

Elasto-plastic simulation of hot shape rolling of steel by a meshless method

This paper describes the development of meshless simulation of thermomechanics of steel in a continuous hot rolling process using a novel meshless solution procedure. During the process, steel billets at high temperatures are transferred through multiple roll passes, each with a specific groove shape and roll gap. The major outcome of this simulation system is to design the rolling schedule and confirm whether the final shape is inside the acceptable range. For this purpose, a perpendicular 2D slice model approach is used to obtain fast and reasonably accurate simulation results. A return mapping algorithm solves the elasto-plastic material model with linear hardening to obtain displacements, strains and stresses. They are calculated by the local radial basis function collocation method (LRBFCM), which uses the local interpolation of the strong form of partial differential equations. The predefined slice positions are entered into the rolling system, and for each position, the slice contact line and amount of reduction are predicted and used as boundary conditions. Thermal and mechanical models are run sequentially, which is repeated until the final slice position reaches the exit from the last roll. The simulation system was validated with multiple rolling schedules provided by the industrial partner and was successfully used in the steel production plant afterwards. The meshless LRBFCM successfully solves a complex elasto-plastic large deformation problem of hot rolling for the first time.

A wall-modeled immersed boundary/large eddy simulation method and its application to simulating heart valve flows

In this work, a wall-modeled immersed boundary (IB)/large eddy simulation (LES) method is extended to the simulation of moving-boundary flows. The used non-equilibrium algebraic wall model is based on an assumed velocity profile, the coefficients of which are determined from physical constraints provided by the full turbulent-boundary-layer equations. To implement the wall model in an IB method named the local domain-free discretization (DFD) method, a local coordinate system fixed on the moving body is introduced. Thus, wall modeling is transformed into a local two-dimensional problem and the complexity of implementation of the wall model is reduced. In the present LES-DFD method, the tangential velocity at an exterior dependent node is determined via wall shear stress prescribed by the wall model. To reduce computational cost for simulating an internal flow with moving boundaries, the stationary boundaries are handled by the body-fitted-grid method and the moving boundaries by the local DFD method. There is no need of an auxiliary grid for solving the non-equilibrium algebraic wall model. Therefore, the inbuilt advantage of an IB method can be retained when simulating moving-boundary problems, and the economy of equilibrium wall models can also be preserved. The present method is applied to simulating the pulsatile flows through a bileaflet mechanical heart valve implanted in a model aorta. The predicted results show an acceptable agreement with the referenced experimental measurements or numerical results at much higher resolution and the applicability of the non-equilibrium wall model to LES of complex moving-boundary flows is verified.

How readers attentive and inattentive to task-related information scan: An eye-tracking study

PurposeAttentive to task-related information should be the highest priority for all readers engaged in task-reading. Investigating the scanning behaviors of attentive versus inattentive readers shed new insights into the sequential cognitive processes, but it has seldom been studied. This study investigates their global patterns on a global scale, pertaining to the whole length of scanpaths, and further compares local tactics, local strategies, and local strategy transitions on a local scale, related to the isolated regions of scanpath. Design/methodology/approachA regular style reading system with the question, navigating, and text areas on its interface, and two types of task, namely fact-finding (FF) and content understanding (CU), were designed in an eye-tracking experiment. 24 participants were placed into attentive (AR) or inattentive (IAR) readers groups according to their fixation duration on task-related paragraphs. A global sequence analysis algorithm, Needleman-Wunsch, was applied to uncover global patterns across the whole length of scanpaths (whole-scanpaths). A local sequence analysis method related to frequent sub-scanpaths was adopted to extract local tactics specific to the reader and task. Coding was performed to identify local strategies by classifying local tactics. A local strategy transition was further identified as a sequence of frequent local strategies at the beginning, middle, and ending phases. FindingsWhole-scanpaths of AR significantly differed from those of IAR, despite the absence of global patterns for each group. Five types of local strategy were identified, namely locating information(LI), evaluating and verifying text relevance (EVR), navigation heuristics (NH), synthesizing information(SI), and contextual clues (CC). AR applied all types in both tasks, whereas IAR applied only two types and stuck with EVR. Furthermore, two types of local strategy transition were identified: comprehensive exploration and iterative content evaluation. AR employed the former with the linear feature in FF and the spiral feature in CU, while IAR employed the latter in both tasks. OriginalityThis study advances the knowledge of dynamic cognitive processing from an attentive and inattentive to task-related information perspective. An objective analysis perspective for obtaining global patterns, local tactics, local strategies, and local strategy transitions is provided, then it can provide new insights into automatically classifying readers. The results also generate detailed and valuable guidance for improving reading system design and training readers.

A diffusion-leakage model coupled with dose point kernels (DPK) for dosimetry of diffusing alpha-emitters radiation therapy (DaRT).

Diffusing alpha-emitters radiation therapy (DaRT) is a novel brachytherapy technique that leverages the diffusive flow of 224Ra progeny within the tumor volume over the course of the treatment. Cell killing is achieved by the emitted alpha particles that have a short range in tissue and high linear energy transfer. The current proposed absorbed dose calculation method for DaRT is based on a diffusion-leakage (DL) model that neglects absorbed dose from beta particles. This work aimed to couple the DL model with dose point kernels (DPKs) to account for dose from beta particles as well as to consider the non-local deposition of energy. The DaRT seed was modeled using COMSOL multiphysics and the DL model was implemented to extract the spatial information of the diffusing daughters. Using Monte-Carlo (MC) methods, DPKs were generated for 212Pb, 212Bi, and their progenies since they were considered to be the dominant beta emitters in the 224Ra radioactive decay chain. A convolution operation was performed between the integrated number densities of the diffusing daughters and DPKs to calculate the total absorbed dose over a 30-day treatment period. Both high-diffusion and low-diffusion cases were considered. The calculated DPKs showed non-negligible energy deposition over several millimeters from the source location. An absorbed dose>10Gy was deposited within a 1.8mm radial distance for the low diffusion case and a 2.2mm radial distance for the high diffusion case. When the DPK method was compared with the local energy deposition method that solely considered dose from alpha particles, differences above 1Gy were found within 1.3 and 1.8mm radial distances from the surface of the source for the low diffusion and high diffusion cases, respectively. The proposed method enhances the accuracy of the dose calculation method used for the DaRT technique.

Heterogeneity constrained color ellipsoid prior image dehazing algorithm

To address the issue of inaccurate transmission estimation in areas with sudden depth changes in hazy images, the image dehazing algorithm with Heterogeneity Constrained Color Ellipsoid Prior (HC-CEP) is proposed. Firstly, a local threshold optimization quadtree search method is designed, in order to solve the problem of inaccurate global atmospheric light estimation and avoid the overall darkening of the image caused by white objects.Then, different regions are selected by a local block heterogeneity window to construct diversity prior vectors to estimate the initial transmission. Finally, by constructing neighborhood heterogeneity weighted constraints on each pixel of the initial transmission and improving the high-order differential filtering of the Scharr operator, the optimization of the transmission is achieved, eliminating halo artifacts in the depth mutation area of the image. Both qualitative and quantitative experimental results show that the proposed algorithm comprehensively considers the heterogeneity of local pixel characteristics, and the dehazing image obtained has better color fidelity and edge detail preservation ability, which can effectively eliminate halo artifacts on the edges of hazy images.The proposed method has better dehazing performance and has a 8% improvement in terms of the FADE metric compared to state-of-the-art dehazing methods.

Simulation of temperature field in steel billets moving in the reheating furnace by a meshless method

A simulation of a reheating furnace in a steel production line where the steel billets are heated from room temperature up to 1200 °C is carried out. In this work, governing equations are solved in a strong form by the meshless local radial basis function collocation method (LRBFCM) with explicit time-stepping. The solution of the diffusion equation for the temperature is formulated on a two-dimensional central slice of the billet. The temperature field is solved by considering the positions of multiple billets in the furnace and the radiative and convective heat fluxes on the boundaries of the furnace and the billets. Ray tracing procedure, in which the view factors are computed with a Monte-Carlo method, is employed to determine the radiative heat flux. A sensitivity study is performed on the influence of two different stopping times of the billets in the furnace on the temperature evolution.

3D Localization and Tracking Methods for Multiplatform Radar Networks

3D Localization and Tracking Methods for Multiplatform Radar Networks

Degradation modeling and remaining useful lifetime prediction based on functional variance process

AbstractDynamic fluctuation is a common phenomenon in degradation processes. Hence, how to model it properly has a great impact on the degradation modeling as well as the remaining useful lifetime prediction. To capture the dynamic features and to avoid the risk of the model mis‐specification, a nonparametric degradation model based on functional variance process is proposed in this article. The model is composed of a unit‐specific mean trend and a degradation fluctuation which follows a stochastic process. The mean trend is estimated by the local smoother method, while the stochastic fluctuation is estimated by the functional principal component analysis method. The asymptotic properties of the estimators are proved. Also, the prediction for the remaining useful lifetime is discussed and the estimator is proved to converge in distribution. Moreover, a Bayesian scheme is developed to forecast the remaining useful lifetime for units with incomplete degradation observations. Simulation results show the superiority of the proposed method by comparing it with some existing methods. Finally, two real data sets are analyzed and used to illustrate the application of the method.

Multi-objective branch-and-bound for the design-for-control of water distribution networks with global bounds

This study investigates a design-for-control (DfC) problem formulation for the joint minimization of pressure-induced leakage, maximization of resilience, and minimization of cost in water distribution networks (WDN). The DfC problem, which consists in simultaneously installing new valves and/or pipes and optimizing valve control settings, results in a challenging optimization problem belonging to the class of non-convex multi-objective mixed-integer non-linear programs (MOMINLP). Due to their complex mathematical structure, multi-objective WDN design-for-control problems have previously been solved using general-purpose evolutionary algorithms or local deterministic methods, which do not provide guarantees on the quality of the returned solutions. While branch-and-bound (BB) frameworks have been proposed to approximate the Pareto fronts of MOMINLPs with global bounds, they rely on the availability of attainable solutions which, for WDN design-for-control problems, can be hard to identify. Moreover, in the absence of general-purpose solvers, the performance of multi-objective BB implementations depends, for a given application, on the choice of adequate branching and lower bounding strategies. In this study, we investigate a multi-objective BB algorithm based on tailored branching, lower bounding and additional upper bounding strategies to efficiently approximate the Pareto front of WDN design-for-control problems with bounds of ϵ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\epsilon$$\\end{document}-non-dominance. The proposed algorithm is applied to the optimal DfC of two case study networks and is shown to outperform alternative solution methods.

Comparison between RBF and FDM for solving nonlinear time-dependent PDEs using Newton’s Method

In this paper, the improved localized method of approximated particular solutions (ILMAPS) using polyharmonic splines with constant polynomial basis is used to approximate solutions of nonlinear time-dependent PDEs. The discretization process is done through a simple implicit time stepping and a collocation technique on a set of points in local domains of influence. Resulted system of nonlinear algebraic equations is solved by Newton’s method. Numerical experiments suggest that the proposed method yields superior accuracy than other RBFs as well as FDM for solving nonlinear PDEs.

A distribution network traveling wave localization method based on CEEMD-DEO3S

A traveling wave head calibration way according to Complementary Ensemble Empirical Mode Decomposition (CEEMD) and Three-point Symmetric Differential Energy Operator (DEO3S) is proposed to address the issues of noise interference and difficulty in precise positioning in local area network wave positioning. The way filters out low-frequency bandwidth in the fault data by performing CEEMD decomposition on the signal and then uses the DEO3S algorithm to define the time of arrival of the fault wave head. The emulation results indicate the proposed way can precisely extract wave heads even in the presence of a large amount of noise interference, and has good robustness and accuracy. Compared with traditional traveling wave positioning methods, it has obvious advantages and further improves the accuracy and reliability of traveling wave positioning.

Application of the localized method of fundamental solutions to heat transfer problems

A localized version of the Method of Fundamental Solutions is applied to the 2D steady heat transfer equation with spatially varying thermal conductivity. Though the corresponding fundamental solution cannot be computed in general, the localization splits the original problem into several subproblems defined on small subdomains; in these subdomains, the subproblems are approximately converted to certain convection-diffusion equations with constant coefficients, so that the Method of Fundamental Solutions is applicable. In each subdomain, the corresponding subproblem is solved separately. This results in an iterative method, which mimics the overlapping (alternating) Schwarz method. Due to its advantageous numerical properties, the technique seems a useful generalization of the Method of Fundamental Solutions. The method is illustrated through numerical examples.

Vision detection and path planning of mobile robots for rebar binding

AbstractFocused on the problems of cumbersome operation, low efficiency, and high cost in the traditional manual rebar binding process, we propose a mobile robot vision detection and path‐planning method for rebar binding to realize automated rebar binding by combining deep learning and path‐planning technology. A MobileNetV3‐SSD rebar binding crosspoints recognition model is built based on TensorFlow deep learning framework, and a crosspoints localization method combining control factor α and feature projection curve is introduced to achieve the localization of unbound crosspoints. In addition, A back‐and‐forth path‐planning algorithm with priority constraints combined with dead zone escape algorithm based on improved A* is proposed to achieve complete coverage path planning of the working area and path transfer of the dead zone. In the field test of the robot prototype, the classification accuracy and localization accuracy reached 94.40% and 90.49%, and the robot was able to reach complete coverage path planning successfully. The experimental results show that the visual detection method can achieve fast, noncontact and intelligent recognition of rebar binding crosspoints, which has good robustness and application value. At the same time, the proposed path‐planning method has higher efficiency in the execution of robot complete coverage path planning, and meets the basic requirements of path planning for rebar binding process.

Research on collaborative localization technology of UAVs based on INS and UWB

The trend of miniaturization and low-cost development in cluster systems restricts the ability of all UAVs within the cluster system to be equipped with expensive high-precision navigation equipment. Relying solely on their low-precision INS (inertial navigation system) will cause navigation errors to quickly diverge. To improve the navigation accuracy of UAVs, a distributed collaborative localization method combining leader and wingman is proposed, and the corresponding mathematical model is derived. The wingman obtains the position information and distance information of the leader through UWB (Ultra-Wide Band) devices and then applies the Kalman filter algorithm to fuse it with its inertial navigation solution information, thereby improving the positioning accuracy of the wingman. On this basis, to address the issue of height channel divergence when the number of leaders decreases, it is proposed to add a barometer and maintain collaborative positioning accuracy by introducing height information assistance. Finally, the feasibility of this method was verified through mathematical simulation, and the simulation results show that compared with inertial navigation, the collaborative navigation and positioning method is more suitable for long-endurance navigation.

Electrical characteristics of ore-forming intrusion No. 2 in the Xiarihamu magmatic Ni-Cu sulfide deposit in East Kunlun Orogenic Belt

The Xiarihamu magmatic Ni-Cu sulfide deposit is situated within the East Kunlun Orogenic Belt and consists of four intrusions. While the estimated Ni resources of intrusion No. 1 exceed 1.2 million tons, the resource potential of other intrusions remains unknown. One significant factor contributing to this knowledge gap is the lack of effective detection and localization methods for concealed intrusions. To address this issue, we conducted an electromagnetic study focusing on intrusion No. 2. Due to the substantial topographic relief in the survey area, the conventional artificial-source electromagnetic method presented limitations in data acquisition. Consequently, we employed the short-offset transient electromagnetic method for data acquisition. A group-network observation mode was utilized to reconstruct the electrical structure of intrusion No. 2 through data inversion. Our results reveal a predominant high-resistivity background within the survey area. Rocks including granite, biotite gneiss, gabbro, and pyroxenite exhibit high resistivities, whereas mineralized ultramafic rocks show lower resistivities due to the presence of sulfides. The detection of concealed conductive bodies serves as a crucial indicator for deep mineral exploration. The distribution characteristics of low-resistivity anomalies indicate that the mafic bodies extend deeper towards the southwest, with mineralized pyroxenites observed beneath the gabbros. The results also suggest a gradual weakening of mineralization from the northeast to the southwest, with conductive mineralized anomalies existing at considerable depths beneath the known exposed intrusion. These findings highlight promising prospecting potential and provide valuable insights into the formation of intrusions within the Xiarihamu deposit, supporting resource exploration in similar deposits.

Multi-sample joint localization method for intrusion sources around underground pipelines based on cross-correlation convolutional neural networks

Improving the safety monitoring of underground pipelines is crucial for maintaining the structural integrity of critical infrastructure systems. This study introduces an innovative multi-sample joint localization method (MSJLM) based on cross-correlation convolutional neural networks (CC-CNNs) to identify intrusion sources in the vicinity of underground pipelines. Traditional approaches to detecting and locating pipeline intrusions often rely on a solitary sensor monitoring point, making them susceptible to errors and limitations. Presently, widely used distributed optical fiber testing methods tend to yield imprecise localization. In contrast, the MSJLM proposed in this study harnesses data from multiple samples effectively and combines them via correlation analyses to enhance precision and reliability. The CC-CNN framework used to process the collected data is demonstrated to be highly effective in extracting spatial features and recognizing patterns.