The development of a simple and efficient methodologies for numerically analyzing the material fracture process is very important in the field of computational mechanics. Damage mechanics approaches are still applied ...
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The development of a simple and efficient methodologies for numerically analyzing the material fracture process is very important in the field of computational mechanics. Damage mechanics approaches are still applied to fracture numerical analyses of many engineering practice problems. This paper focuses on the numerical prediction of crack propagation and fracture behavior by the combination of anisotropic damage model and tracking algorithm. In general, anisotropic damage models may be misunderstood to be used only in the simulations of anisotropic materials. However, it can be used for the anisotropic stiffness matrix induced by the crack plane in damaged isotropic materials. Although it is well known that the anisotropic damage model is superior to the isotropic damage model in fracture simulations, most of studies have combined the isotropic damage model and tracking algorithm, and few studies combine the anisotropic damage model and tracking algorithm. The issues of successfully combining the anisotropic damage model and crack tracking algorithm are addressed in this study. The anisotropic damage model is improved and a local tracking algorithm based on crack surface discretization is also modified. Various crack propagation problems are analyzed numerically to demonstrate the superior performance of the proposed approach.
We develop a fully Bayesian tracking algorithm with the purpose of providing classification prediction results that are unbiased when applied uniformly to individuals with differing sensitive variable values, e.g., of...
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We develop a fully Bayesian tracking algorithm with the purpose of providing classification prediction results that are unbiased when applied uniformly to individuals with differing sensitive variable values, e.g., of different races, sexes, etc. Here, we consider bias in the form of group-level differences in false prediction rates between the different sensitive variable groups. Given that the method is fully Bayesian, it is well suited for situations where group parameters or regression coefficients are dynamic quantities. We illustrate our method, in comparison to others, on simulated datasets and two real-world datasets.& COPY;2022 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
In the past few decades, target tracking algorithm has been paid great attention by peers at home and abroad in the field of computer vision because of its potential for in-depth research and practical value. Typical ...
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In the past few decades, target tracking algorithm has been paid great attention by peers at home and abroad in the field of computer vision because of its potential for in-depth research and practical value. Typical applications of target tracking algorithms include intelligent video surveillance, autonomous vehicles, human-computer interaction and so on. Given the initial state of a target object, the task of the target tracking algorithm is to estimate the state of the target in the subsequent video. Despite years of efforts, designing a target tracking algorithm is still a very challenging problem, because it poses changes, particularly illumination changes, and in addition, occlusion, complex environments, and the moving background will also cause changes in the appearance of the target. The traditional target tracking algorithm based on manually designed features or shallow classifiers uses manually designed low-level visual features or shallow classifiers to build the target apparent model, so the semantic information prediction ability of the target apparent model is limited. Given the defect that the above traditional target tracking algorithm is difficult to capture the semantic information of visual data in the target apparent model, inspired by the great success of deep convolution networks in image classification and speech recognition, a target tracking algorithm based on convolution neural network is proposed in this paper.
In this paper we present the design, implementation and preliminary tests of a high depth underwater ROV inspection system. The ROV is equipped with a sensor-based system in order to characterize the water quality of ...
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ISBN:
(纸本)9781665418218
In this paper we present the design, implementation and preliminary tests of a high depth underwater ROV inspection system. The ROV is equipped with a sensor-based system in order to characterize the water quality of marine ecosystems, and a vision-based system to identify the marine species. The vision system includes an adaptive color correction algorithm and a tracking algorithm that improves in real time the tracking of living species during inspection. A prototype was implemented to validate the functionality of the ROV operation and the vision system algorithms.
In this paper, a hybrid weight design and optimization mechanism is proposed to ensure a better application effect in the multi-level weighted evaluation/optimization process of intelligent neural network (NN) guidanc...
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In this paper, a hybrid weight design and optimization mechanism is proposed to ensure a better application effect in the multi-level weighted evaluation/optimization process of intelligent neural network (NN) guidance algorithm. According to different target tracking scenarios, the tracking index are divided into different periods, a single period score is given according to a linear-nonlinear hybrid scoring mechanism. Furthermore, in a single index, the internal scores of different time periods are weighted and fused for the second time to obtain the index overall score. Finally, the third weighted fusion of the multi-index scores is used to obtain the comprehensive score of the algorithm. Design the algorithm parameter evaluation case sets, repeat the above compound weighting, obtain the case with the highest comprehensive score. Finally, the algorithm is optimized by the highest score case. In the hybrid weight design mechanism, the objective grey correlation first defines the weight range, then the subjective expert decision method with local extreme expert elimination and standard deviation global test for double optimization finally ensures the weight reliability of the hierarchical evaluation optimization. The evaluation optimization experiment using fuzzy NN radar seeker verifies the effectiveness of the method.
Multi-target tracking is a complex problem in computer vision, involving occlusion, target trajectory disappearance, etc. In response to these questions, we first propose a trajectory coordinate bi-directional sensing...
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Multi-target tracking is a complex problem in computer vision, involving occlusion, target trajectory disappearance, etc. In response to these questions, we first propose a trajectory coordinate bi-directional sensing attention module (BasicCaModule). This module enables the network to be more focused on essential areas. Secondly, we propose the Feature Confusion Edge Enhancement (FCEE) module, which enhances the confusion region of adjacent feature edges. After detecting the network output feature map, we propose the adaptive feature separation header (FDH) module. This module can activate essential features adaptively to reduce the number of target identity switches. Finally, appropriate hyperparameters are set and optimized for the ByteTrack tracking algorithm, resolving fragment tracking loss and long memory matching problems. After a large amount of experimental data, our approach is highly competitive with the existing state-of-the-art algorithms. Moreover, it can also keep online tracking while maintaining high tracking accuracy. The code is publicly available at: https://github .com / CccJ23 /Spatio -temporal -trajectory-tracking (c) 2023 Elsevier Inc. All rights reserved.
In a departure from the past, unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs) are increasingly needed for complementary cooperation in military, scientific, and commercial applications, becaus...
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In a departure from the past, unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs) are increasingly needed for complementary cooperation in military, scientific, and commercial applications, because this is more efficient than standalone operations. Information sharing through acoustic underwater communication is vital for complementary cooperation between USVs and UUVs. Normally, since USVs have advantages in terms of wide operational boundaries compared to UUVs, they are efficient for tracking UUVs. In this paper, we suggest a UUV tracking algorithm for a USV. The tracking algorithm's development consists of three main software models: an estimation based on an extended Kalman filter (EKF) with a navigation smoothing method, guidance based on multimode guidance, and re-searching based on a pattern. In addition, the algorithm provides a procedure for tracking UUVs in complex acoustic underwater communication environments. The tracking algorithm was tested in a simulated environment to check the performance of each method, and implemented with a USV system to verify its validity and stability in sea trials. The UUV tracking algorithm of the USV shows stable and efficient performance.
In this paper, a stair-planar phased array antenna system for mobile broadcast satellite reception in Ku-band is proposed. The hybrid electromechanical tracking algorithm of this antenna system is designed for properl...
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In this paper, a stair-planar phased array antenna system for mobile broadcast satellite reception in Ku-band is proposed. The hybrid electromechanical tracking algorithm of this antenna system is designed for properly steering the antenna beam into the target satellite. The antenna sub-array elements are designed by using FR-4 epoxy and RO4003 to reduce the fabrication cost without considerable drop in the array efficiency. The genetic algorithm optimization is used to achieve the optimum values for the element spacing and feed positions, also. This array is fabricated, tested and compared with the simulation results to prove the idea. After that, the selected array is expanded to the main sub-array (2 x 32) and the main antenna array composed of 640 microstrip elements (10 main sub-arrays with 64 elements in each sub-array) with 32.5-dB gain at operating frequency, 11.9 GHz. This system can cover 30 degrees-70 degrees in elevation and 360 degrees in azimuth planes by using the hybrid tracking algorithm to track different target satellites. This system serves as an excellent low-cost and simple candidate for Ku-band satellite reception in steady and smoothly moving platforms such as trains.
As a dominant type of disturbance during aircraft braking, variation in maximum friction between the runway and the tires largely affects the efficiency of aircraft anti-skid braking systems (ABS). Conventional aircra...
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As a dominant type of disturbance during aircraft braking, variation in maximum friction between the runway and the tires largely affects the efficiency of aircraft anti-skid braking systems (ABS). Conventional aircraft anti-skid braking control method, such as pressure-bias-modulated (PBM), are unable to identify and track the changing maximum friction between the runway and the tires, which results in reduced braking efficiency and long braking distances. This paper presents a novel anti-skid braking control method which can identify and track the maximum friction using only wheel angular velocity and brake pressure signals. An extended braking stiffness (XBS)-based runway maximum friction identification method is proposed to determine the runway maximum friction, where XBS is the differential of the friction to the differential of the slip ratio. tracking differentiator (TD) is employed to derive the corresponding differential signals, which enables XBS to be calculated efficiently, without compromising calculation accuracy. By analyzing the dynamic characteristic of the wheel, a runway friction characteristic observation function is designed to observe changing friction characteristic during the entire braking. To be able to track the varying maximum friction in real time, a runway maximum friction tracking algorithm is designed, which can realize accurate brake pressure control according to the change in runway friction characteristic. The Lyapunov function is employed to prove the stability of the designed controller. Simulation tests are carried out under multiple sets of changes in runway friction characteristic. The comparison simulation test with PBM algorithm shows that the designed control method greatly improves the braking efficiency. Ground inertia test bench experiments are also conducted to further verify the correctness and effectiveness of the proposed aircraft anti-skid brake control method. Simulation and experiment results prove that the propos
Collecting data like location information is an essential part of concepts like the "IoT" or "Industry 4.0". In the case of the development of a precise localization system and an integrated naviga...
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Collecting data like location information is an essential part of concepts like the "IoT" or "Industry 4.0". In the case of the development of a precise localization system and an integrated navigation system, indoor location technology receives more and more attention and has become a hot research topic. Common indoor location techniques are mainly based on wireless local area network, radio frequency tag, ZigBee technology, Bluetooth technology, infrared technology and ultra-wideband (UWB). However, these techniques are vulnerable to various noise signals and indoor environments, and also the positioning accuracy is easily affected by the complicated indoor environment. We studied the problem of real-time location tracking based on UWB in an indoor environment in this paper. We have proposed a combinational filtering algorithm and an improved Two-Way Ranging (ITWR) method for indoor real-time location tracking. The simulation results prove that the real-time performance and high accuracy of the presented algorithm can improve location accuracy. The experiment shows that the combinational algorithm and ITWR method which are applied to the positioning and navigation of the smart supermarket, have achieved quiet good results in positioning accuracy. The average positioning error is less than 10 cm, some of the improvements can elevate the positioning accuracy by 17.5%. UWB is a suitable method for indoor real-time location tracking and has important theoretic value and practical significance.
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