bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anomaly detection of four-engine aircraft based on Parameter differences
Authors: Liu Jiahuan , Bai Jie , Wang Wenjin 
Published: July 2024

Abstract
In this paper, a real-time anomaly detection method combining GDN and Gaussian model is proposed for the real-time engine condition monitoring of four-engine aircraft. Firstly, the gas path parameters of the engine are selected and the difference of the gas path parameters is calculated to offset the influence of the external environment on the engine. Thirdly, the sliding time window method is used for real-time prediction, and the model prediction residuals are used for unsupervised anomaly detection. Finally, the Gaussian model is used to prune the anomalies detected by the GDN model to reduce the misjudgment of anomalies and improve the accuracy of anomaly detection. The experimental results show that the proposed method can detect 97.96% of the outliers in the test set and the accuracy reaches 89.47%, which is better than LSTM, AE, GDN, and Gaussian models alone.
Design and simulation of AGV control system based on V-REP
Authors: Zhu Jianchao , Yang Chen , Cao Zifan , Jiang Bo , Xue Yanjie , Lin Zhuorui 
Published: July 2024

Abstract
In this paper, the design and simulation method of the AGV control system is studied, a variable gain PID control method for the AGV-oriented speed control system is designed, a three-dimensional AGV model in the V-REP simulation platform is established for the directional control system, and a control strategy is designed. Finally, the AGV control system is simulated based on the V-REP simulation platform. The simulation results show that the control system in V-REP has a good control effect on AGV.
Driverless holographic simulation test integrated environment design
Authors: Leng Sixuan , Mo Liye , Pan Xiang , Lin Xingzhi 
Published: July 2024

Abstract
Aiming at the design problem of simulation test integrated environment for unmanned car, starting from the four aspects of unmanned simulation test [1], real scene quiz, scene analysis and layout, and data visualization and processing, through the combination of software and hardware, the use of various types of sensors, controllers, communication equipment, etc. for collaborative management of unmanned car driving, and the use of intelligent networked cars to collaboratively verify the multi-class algorithms and driving programs, and continuously improve the Overall environment design [2] [3], the integrated environment design is getting better and better. This overall environment is tested based on carla’s Apollo autonomous driving simulation software, and the test results show that the recognition accuracy rate reaches 87% and the simulation rate reaches 91%, etc. It shows that the unmanned holographic simulation test integrated environment technology program is feasible.
Numerical simulation of neural activity based on discrete Markov chains with stochastic differential equations
Authors: Wang Erhui , Luan Xuefei 
Published: July 2024

Abstract
With the development of new numerical calculation methods and computer software science and technology, people can have a good understanding of the potential mechanisms of cerebrovascular diseases. Here, we combine the stochastic differential equation (SDE) of discrete Markov chains to numerically simulate the dynamic changes of neural signals, and find that the changes of neural signals exhibit regular fluctuations. By analyzing the variation of voltage over time, we know that the voltage change at the next moment is closely related to the previous moment and has continuity. Based on the knowledge of neural ion channel dynamics, it was found that there will be longer peak changes in voltage, exhibiting a power-law distribution, which is consistent with the actual situation and statistical data related to resignation channels. By analyzing the voltage and peak changes of ion channels, we can gain a new understanding of the transmission laws of neural information and greatly improve the biological mechanisms.
The spectral conjugate gradient method in variational adjoint assimilation for model terrain correction III: convergence analysis
Authors: Tao Sulin , Li Yuhong 
Published: July 2024

Abstract
In the former parts of this paper, the spectral conjugate gradient (SCG) algorithm was proposed to identify the optimal bottom terrain used for predicting the meteorological fields. In this part, the convergence analysis of the SCG method is presented to verify its validity when solving a typical ill-posed inverse problem. The scaled cost function, the scaled gradient norm, the linear convergence rate, and the Hessian approximation condition number are evaluated for convergence analysis. The SCG method reduces the cost functional value and the gradient norm sufficiently. It always performs linear rates of convergence with a quickly reduced condition number of the Hessian matrix. Sometimes it provides very fast linear convergence rates. The SCG code with optimal step size and Andrei’s equation is effective on ill-posed test problems.
Numerical analysis and calculation of fractional neuron transmission model
Authors: Wang Erhui , Luan Xuefei 
Published: July 2024

Abstract
It is well known that the transmission of nerve signals is closely related to the incidence and production of vascular diseases. However, due to the multilayered and complex structure of the vascular wall, although a series of studies have been carried out, the mechanism of vascular diseases is difficult to fully understand. In this paper, the fractional constitutive equation is used to study numerically the transmission of nerve signals in the vascular wall. On the basis of considering the effect of substance transport in the vascular layer, a new comprehensive model was established to describe and analyze the voltage trajectory of neuron activity using multi-time-scale dynamics induced by correlated membranes combined with non-Markov processes. The results show that our fractional order model can better describe the process of neurotransmission. By changing the fractional order, we can show in vitro the up-and-down spike adaptation found in the experiments of neocortical pyramidal cells and parietal neurons.
Formal modeling and verification method for Simulink-MDL requirement model
Authors: Li Junan , Hu Jun , Wang Lisong , Wang Kangxing , Dai Jialei 
Published: July 2024

Abstract
As complex safety-critical system software becomes more powerful, so does the complexity of its design requirements. Modeling and analyzing design requirements at an early stage has become an integral part of the entire development process for complex safety-critical system software. Simulink is a system modeling and simulation tool used in aviation and other fields. Its model is stored in the form of MDL files. ART (Avionics Requirement Tools) is a requirement modeling and analysis verification tool for the aviation field. It uses VRM (Variable Relation Model) as the theoretical model and can accept VRM and its extended subsets as input models and verify them in the tool. The work of this paper is oriented to the typical software requirements in the field of avionics systems and proposes a formal modeling and verification method for Simulink-MDL models. First, the composition form and structure of the MDL model are analyzed in the article. The functions and semantics of various elements in the model are given. Then a formal modeling method of the MDL model is given. Finally, a simplified version of the flight guidance control system is used for modeling and verification to demonstrate the usability and effectiveness of this method.
LPI radar waveform recognition model based on multiple feature image and quasi-residual attention module
Authors: Li Zhe , Wu Lihua , Xia Bin , Song Lintao 
Published: July 2024

Abstract
Detecting and classifying the modulation type of the intercepted noisy LPI radar waveform has become a hot topic in the field of Electronic Countermeasures (ECM). In this paper, we propose a recognition model based on multiple feature images (MFI) and convolutional neural networks (CNN) with the quasi-residual attention module (QRAM). The core technologies of this model are divided into two parts. One is the MFI that combines the ambiguity function image (AFI) of the complete signal, covariance matrix image (CMI) of the reconstructed signal, and short-time Fourier transform image (STFTI) of the truncated signal into RGB color image in signal processing as the input for recognition network. The other is CNN with a QRAM recognition network, in which the input is sliced into two mappings called identity mapping and residual mapping to build the quasi-residual module, and the attention module is embedded in each mapping to denoise and enhance the feature. The performance of the MFI-QRAM model is demonstrated by recognizing 12 modulation types of the signals defined in this paper. The simulation experiments show that the model has strong robustness with the number of train sets and the variation of SNR. The overall probability of successful recognition (PSR) is 96.17% when the SNR is −6 dB.
Reliability analysis and optimization of BGA solder based on finite element simulation
Authors: Lei Ting , Yang Jiepeng , Liang Shizhang 
Published: July 2024

Abstract
For the reason of reliability improvement of BGA solder, ANSYS is used to establish a BGA solder model that contains information such as size, material, grid, etc. The thermal stress of solder is selected as the optimization objective by the optimization parameters of solder height, solder radial direction, and spacing of solder. Response surface methodology is used to design 17 sets of different level parameters for simulation calculations, and a regression equation between solder joint stress and optimization parameters is established to obtain the parameter combination with the minimum stress of solder. The analysis results show that the corner solder far from the chip are critical solder joint for failure. The optimized solder joint parameters are as follows. The solder height is 0.5 mm, the solder radial is 0.6 mm, and the solder spacing is 1 mm. The optimized solder joint stress value is 30.818 MPa, which reduces the stress by 27.71% compared to before optimization, which achieved the reliability improvement of BGA solder.
Research on natural ventilation of a community library related to epidemiological insight by using CFD simulation method
Authors: Deng Jie , Vongphantuset Jirawat , Sirivesmas Veerawat , Fang Lin , Guo Zhengquan 
Published: July 2024

Abstract
Spreading through airflow is one of the most common routes for the transmission of viruses, which may result in serious public health problems. To acquire a healthy space for the community library, designing a reasonable ventilation system is a vital measure which can reduce the risk of transmission of the virus effectively.
The purpose of this research is to study natural ventilation methods in an epidemiological insight for the design of a healthy community library by using computational fluid dynamics (CFD) software SOLIDWORKS Flow Simulation. Five typical opening types of windows were selected and studied in the research on the ventilation of the yoga room of a community library, with airflow evaluated by the ACH method, so as to search for the most suitable window type to avoid airborne virus transmission.
The results acquired by SOLIDWORKS simulation showed that 75%, 90%, and 100% openings corresponding to Jalousie, casement, and double casement window types respectively are optimal in community space. The natural ventilation design by proper windows can be applied in the community library and other public spaces.
Simulation of ideal blackbody based on multi-space boundary condition in FDTD
Authors: Wang Nan , Zhu Hongxian 
Published: July 2024

Abstract
Investigation shows that it is difficult to solve the electromagnetic field surrounding an ideal blackbody using the analytic method. To solve this problem, the simulation method should be adapted, and the Maxwell function should be expanded to multi space. In this paper, a multi space simulation scheme of finite difference time domain (FDTD) and a multi space boundary condition (MSBC) are proposed for the simulation of an ideal blackbody. Compared with the traditional absorbing boundary condition (ABC) or perfectly matched layer (PML), which can only be assigned in the outermost layers of the simulation space, the proposed MSBC is simpler and can be arranged inside the computing space. Numerical simulation shows that MSBC has good electromagnetic wave absorption performance and can simulate the ideal blackbody accurately. At the same time, the simulation results also show some interesting characteristics of electromagnetic waves around the ideal blackbody.
Calibration of discrete element method simulation parameters for lunar rover using simulated lunar soil
Authors: Zhao Liangliang , Zhang Hua , Ma Jia , Du Yupei , Hu Zhenyu , Zhang Rui , Zhou Guifen 
Published: July 2024

Abstract
To ensure the accuracy and scientific validity of simulation results in discrete element simulation of simulated lunar soil and sieve wheels for lunar surface probes, a method for calibrating the simulation parameters of an analog lunar soil simulation using a box-Behnken experimental design is proposed. First, the particle model and particle size distribution of the discrete element simulation were calibrated based on the determination of the intrinsic parameters, shape parameters, and particle size parameters of this simulated lunar soil. A Box-Behnken experimental design is employed to conduct response surface simulation experiments for the pile angle, obtaining optimal parameter values. The optimal parameter values are applied in the simulation validation, revealing a relative error of only 3% compared to the actual pile angle. This indicates that the obtained results can serve as calibrated values.
Research on experimental evaluation model of unmanned aerial vehicle autonomy based on digital twin
Authors: Zhang Lu , Wang Hao , Zhai Mingda , Yi Pinglang , Meng Chuanshu 
Published: July 2024

Abstract
The current focus of unmanned aerial vehicle (UAV) research lies in the scientific evaluation of UAV autonomy and the enhancement of belief in UAVs. Researchers are required to conduct numerous tests to assess the ability of UAVs to perform missions in complex environments. However, conducting real-world tests for UAVs costs a lot. Therefore, digital twin virtual simulation serves as a viable alternative to actual flight tests. Firstly, this paper establishes a digital twin framework that enables comprehensive perception and integration within a virtual environment, proposing a UAV autonomy experimental evaluation model. Additionally, an effective method for evaluating UAV autonomy is constructed, and test tasks targeting autonomous capability assessment are designed by using simulation software and verified through system examples. Finally, based on the simulation results, the autonomous capability of the UAV twin is evaluated and utilized as a reference for assessing the autonomy of physical UAVs, thereby providing support for scientific evaluation.
Evaluation of adaptability of software-defined telemetry systems for operational use
Authors: Wang Wanli , Li Yiyong , He Rong , Li Jian , Hu Jingjing 
Published: July 2024

Abstract
Aimed at solving the key problem of operational adaptability assessment of software-defined telemetry systems, the evaluation method of improved hierarchical method and fuzzy comprehensive evaluation is proposed. In the “general + expand + unique” flexible method to build an index system, the “expert decision matrix” index weight assignment and the fuzzy comprehensive evaluation method using operational adaptability assessment are used. According to the principle of maximum membership, the calculation results tend to be the largest. The proportion of 0.6524 shows that the equipment’s operational performance is good. At the same time, it was found that the proportion of qualified was 0.157, exposing its weaknesses and putting forward targeted suggestions, which provided a reference for the technical optimization and improvement, and forward-looking deployment of new equipment.
Estimation of winter wheat yield in Hebi city based on crop models and remote sensing data assimilation
Authors: Li Ying , Zou Chunhui , Feng Liping , Yao Xiaochuang , Li Tongxiao , Chen Xianguan , Zhao Jin 
Published: July 2024

Abstract
Assimilating remote sensing data with crop models is an effective approach to improve the accuracy of crop model applications at the regional scale. Sobol global sensitivity analysis and Markov Chain Monte Carlo methods were used to calibrate parameters in the WOFOST and WheatSM models within a gridded model framework in the study area. Time series data reconstruction techniques were employed to correct MODIS LAI and ET data. Four assimilation scenarios were tested, including assimilation of only leaf area index (LAI), assimilation of only evapotranspiration (ET), simultaneous assimilation of LAI and ET and a control scenario without assimilation. These scenarios were applied to model winter wheat yields in Hebi City, China, from 2013 to 2018. Statistical validation demonstrated that assimilating ET or LAI individually significantly improved model accuracy compared to the control scenario with similar levels of improvement. The highest model accuracy was achieved when assimilating both ET and LAI simultaneously, showing the highest correlation coefficients and the lowest root mean square errors among the four scenarios. This research provides a basis for selecting assimilation variables when applying crop models at the regional scale. The coupling of crop growth models with remote sensing data empowers governments and agricultural producers to devise more effective agricultural strategies, allocate resources efficiently, and implement disaster response measures. This enhances scientific management within the agricultural sector, promotes increased food production and elevates farmers’ incomes.
Temporal Estimators of Peculiar GRBs
Authors: Noriega N. , Cárdenas E. F. , Chacón J. A. , Vásquez N. 
Published: July 2024

Abstract
In our study, we analyze four peculiar Gamma-Ray Bursts (GRBs), namely GRB070724A, GRB070429B, GRB090426, and GRB120804A, all detected by the Swift space telescope. The focus of our investigation lies in evaluating the temporal estimators, such as emission time and spectral lag time in the third Swift GRB catalog sample. Our findings reveal that the calculated temporal estimators offer diverse insights into the classification of the examined GRBs, hinting at the distinctive nature of these events. This suggests that these GRBs can be considered as ‘peculiar’ when compared to standard GRBs in the spectral plane, specifically in the Amati-like relation. Whereas, the spectral lag analysis of the four GRBs increases the evidence to consider these as ‘peculiar’.
Cross-correlation between the multifractal spectra of the solar wind magnetic field from Parker Solar Probe and Solar Orbiter
Authors: Andy Rubio E. 
Published: July 2024

Abstract
The solar wind, a plasma emanating from the Sun and extending throughout the universe, continues to be a subject of intense study. This study focused on examining the multifractal spectra of the solar wind’s magnetic field in regions proximal and distal to the Sun, leveraging data collected by the Parker Solar Probe and Solar Orbiter satellites, respectively. Utilizing the box-counting method within multifractal analysis has provided insights into the distinctive characteristics of each satellite, including singularity exponents and multifractal spectra. However, the cross-correlation observed between the spectra obtained by both satellites has prompted further inquiry into its physical implications. This suggests the need for a more comprehensive investigation to elucidate the underlying dynamics driving these correlations and their significance in our understanding of solar wind behavior. Continued research in this area holds promise for advancing our comprehension of solar phenomena and their broader implications.
Galactic Superbubbles in 3D: Wind Formation and Cloud Shielding
Authors: Suárez-López O. , Villares A. S. , Banda-Barragán W. E. 
Published: July 2024

Abstract
Galactic superbubbles are triggered by stellar feedback in the discs of star-forming galaxies. They are important in launching galactic winds, which play a key role in regulating the mass and energy exchange in galaxies. Observations can only reveal projected information and the 3D structure of such winds is quite complex. Therefore, numerical simulations are required to further our understanding of such structures. Here, we describe hydrodynamical simulations targeting two spatial scales. Large-scale superbubble models reveal supernova-driven outflows, and their subsequent merging, which leads to galactic wind formation. Additionally, the turbulence parameter σt
not only affects disc formation, but also influences mass and energy characteristics, controlling gas distribution and the injection rate in the simulated star formation zone. Small-scale wind-multicloud models indicate that isolated clouds are susceptible to instabilities, leading to fragmentation and dense gas destruction. In contrast, in closer cloud configurations, the condensation mechanism becomes important owing to hydrodynamic shielding, which helps to maintain the cold material throughout the evolution of the system. These simulations provide a comprehensive picture of galactic winds, showing how large-scale superbubble dynamics create the environment where small-scale wind-multicloud interactions shape the interstellar and circumgalactic media, ultimately regulating galaxy evolution.
Exploring the Universe through Gamma-Ray Astronomy: Characterization and Performance of the LST-1 Telescope
Authors: Baquero Larriva A. , Contreras J.L. ,   CTA-LST Project
Published: July 2024

Abstract
Gamma-ray astronomy allows for the exploration of the most energetic phenomena in the universe and has seen significant advances in the 21st century, as evidenced by the development of the LST-1 telescope, a part of the Cherenkov Telescope Array (CTA). The LST-1, situated at the Roque de los Muchachos Observatory in La Palma, Spain, commenced its commissioning phase in October 2018 and captured its first light in December of the same year. This research primarily addresses the characterization of the LST-1 telescope, utilizing Monte Carlo simulations and real data from observations of the Crab Nebula to assess its performance, which is already approaching the design requirements. Furthermore, the results obtained from observations of the Active Galactic Nuclei Markarian 421, Markarian 501, and 1ES 1969+560 agree with those obtained by other telescopes, thus validating the efficacy of the LST-1.