bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical simulation of multi-carrier microwave breakdown in air-SF6 mixtures
Authors: Wang Lin , Bao Huaguang , Ding Dazhi , Chen Rushan
Published: September 2021

In this paper, the multi-carrier microwave breakdown in air-SF6 mixtures is analyzed with the spectral-element time-domain method. In this process, a three-dimensional multi-physics model coupling Maxwell's equations with electron fluid equations is established. The tail-erosion and frequency shift phenomenon caused by multi-carrier microwave breakdown in different proportions of air-SF6 mixtures can be observed. Numerical results demonstrate that multi-carriers will make the wireless communication system sensitive to microwave breakdown. On the other hand, the different proportions of air-SF6 mixtures can obviously improve the breakdown threshold to inhibit the multi-carrier microwave breakdown, which is favorable to the propagation of multi-carrier microwaves in air. Meanwhile, increasing the pressure can suppress the frequency shift phenomenon, and the proportion of different SF6 in the mixed gas has little effect on the frequency shift of the transmitted wave. Our research provides theoretical guidance for comprehensively exploring the characteristics and physical mechanism of multi-carrier microwave breakdown in air-SF6 mixtures and is helpful for protection of microwave devices and plasma application.
Effect of the density ratio variation on the dynamics of a liquid jet injected into a gaseous cross-flow
Authors: Tretola Giovanni , Vogiatzaki Konstantina , Navarro-Martinez Salvador
Published: September 2021

In this paper, we investigate the effect of the density ratio on the primary atomization characteristics of a liquid jet injected into a gaseous crossflow. Jets into crossflow with a high density ratio can be challenging for some multiphase models with an interface reconstruction. In this case, it is common practice to artificially reduce the density ratio, keeping constant the dominant non-dimensional parameters, based on the assumption that keeping unaltered the non-dimensional numbers will also maintain the same atomization characteristics. The validity of this assumption is here investigated using large eddy simulations and a stochastic fields transported probability density function (PDF) method (Σ-Y-PDF). A jet into crossflow, with a momentum flux ratio of 6.6 and Weber number of 330, is simulated. Two different density ratios are considered, 10 and 860, corresponding to the ones adopted in previous detailed numerical simulation and experimental investigations, respectively. We find that the liquid column breakup is influenced by the density ratio, with lateral ligaments formation observed only for the lower one. Also, the flow field is affected: decreasing the density ratio, the velocity increases in the wake region with recirculation observed. Furthermore, despite having the same Weber and Reynolds numbers, the two cases show different droplet size distributions. Smaller droplets are produced with the increase in the density ratio. Close to the liquid jet, the shape of the distribution is also affected. For the lower density ratio, a dichotomy is present, related to the presence of two distinct underlying breakup mechanisms, while increasing the density ratio, the dichotomy disappears.
Instability of cumulation in converging cylindrical shock wave
Authors: Chefranov Sergey G.
Published: September 2021

The conditions of linear instability for a converging cylindrical shock wave in an arbitrary inviscid medium are obtained. The initial continuous cylindrical symmetry of the shock wave front is exchanged on a discrete symmetry that is determined by the most unstable small azimuthal dimensionless wave numbers 0<k<kth<1 of corrugation perturbations. Due to the long azimuthal wavelengths (λ=2πRs0/k, Rs0—the radius of the shock wave) of perturbations, the shape of the resulting shock wave front is not changed significantly, but the corresponding restriction of the internal energy cumulation can be caused by the intensification of the rotation of the medium behind the front. The instability and the restriction of cumulation are also possible in the case of the exponential rapid growth of the one-dimensional perturbations with k=0, when the shape of the shock front is not changed at all. The correspondence of present theory to the experimental and simulation data on underwater electrical explosion is considered.
Energy insights into the unsteady dynamics of a viscous gravitational liquid sheet
Authors: Della Pia Alessandro , Colanera Antonio , Chiatto Matteo , de Luca Luigi
Published: September 2021

The impulse response of planar liquid sheet flows, subjected to gravity, and interacting with unconfined gaseous environments located on both sides of the liquid phase, is numerically investigated from an energy perspective by means of a combined approach of linear stability analysis and direct numerical simulations, carried out with the volume-of-fluid technique. The computation of global eigenmodes and eigenvalues is based on a simplified one-dimensional model also accounting for viscous effects. Physical insights are gained by means of an original energy balance equation for sinuous perturbations, identifying the energy budgets associated with the different terms governing the flow dynamics. Two distinctive features of the sheet flow, the flow instability in the supercritical regime at relatively high gas-to-liquid density ratio and the discontinuity in frequency at the supercritical-to-subcritical transition, have been recovered and discussed. The pressure work is responsible for the instability of supercritical regimes at relatively high density ratio. This finding is confirmed by the direct numerical simulations, showing a convective amplification of the perturbation as it travels downstream: for high density ratios, the large convective amplification cannot be expelled from the domain and the flow suffers from a global instability. The frequency discontinuity occurring at the supercritical-to-subcritical transition is basically due to the left-going wave expulsion; therefore, the subcritical sheet stabilizes more rapidly than the supercritical one, and the slow branch of the spectrum disappears. The high frequency oscillations observed in subcritical regime are attributed to the removal of constraint on the meanline slope when We < 1, which produces an increase in the oscillation frequency of the sheet analogous to that occurring for elastic solid beams when the clamped constraint is substituted by pinned constraint.
Diffusive fluxes and water-extractable concentrations of different nitrogen forms in a temperate agricultural soil
Authors: Inselsbacher Erich , Peticzka Robert
Published: September 2021

Synchronising nitrogen (N) fertiliser inputs and crop N demand is a major goal in intensive agriculture. However, assessing how much and in which form N arrives at the root surfaces remains a major challenge. Microdialysis has been introduced as a suitable technique to face this challenge and, in this study, we applied microdialysis to assess in situ diffusive N fluxes in a temperate agricultural field. Additionally, soil N concentrations were estimated by water extractions to compare different approaches for measuring plant-available N. Concentrations and diffusive fluxes of N did not correlate and differed significantly regarding the relative contribution of different N forms to total N. Nitrate was the dominant N form (∼80%) in water extracts while diffusive fluxes of NO3−, NH4+ and free amino acids were similar (38%, 34% and 28%, respectively). Extractable N and diffusive N fluxes varied strongly across the entire field, with a higher variability at smaller scales. Our results suggest that diffusive N fluxes are affected by a complex network of abiotic and biotic factors, either directly controlling diffusion or indirectly by affecting soil N production and consumption rates. We therefore recommend that future efforts should be directed into including such factors in more complex modelling approaches to assess plant-available N in agricultural fields.
Selective depletion of a CD64-expressing phagocyte subset mediates protection against toxic kidney injury and failure
Authors: Salei Natallia , Ji Xingqi , Pakalniškytė Dalia , Kuentzel Vanessa , Rambichler Stephan , Li Na , Moser Markus , Steiger Katja , Buch Thorsten , Anders Hans-Joachim , Schraml Barbara U.
Published: September 2021

Significance

There continues to be a paucity in models to target mononuclear phagocyte (MP) subsets selectively and in specific tissues. We report a mouse model allowing for selective depletion of a specific subset of kidney MPs that is based on a Cre-inducible lox-STOP-lox-diphtheria toxin receptor gene controlled by the endogenous CD64 promoter. Combined with specific targeting of conventional DC1 (cDC1) and cDC2, we revealed that CD64
+
MPs account for the reported ability of CD11c
+
cells to limit cisplatin nephrotoxicity, while cDC1 and cDC2 are dispensable. Our study highlights that individual MP subsets have unique functions in kidney pathology. Combined with various CRE drivers, CD64-lox-STOP-lox-diphtheria toxin receptor mice might be used to study CD64-expressing cells in other tissues.
Defective myelination in an RNA polymerase III mutant leukodystrophic mouse
Authors: Merheb Emilio , Cui Min-Hui , DuBois Juwen C. , Branch Craig A. , Gulinello Maria , Shafit-Zagardo Bridget , Moir Robyn D. , Willis Ian M.
Published: September 2021

Significance

Pathogenic mutations in subunits of RNA polymerase (Pol) III cause a prevalent autosomal recessive form of leukodystrophy. However, understanding of the mechanisms of pathogenesis, including how ubiquitously expressed Pol III mutations affect primarily the central nervous system, has been limited by the absence of an animal model of the disease. We show that conditional knockin of pathogenicPolr3amutations in the Olig2 lineage in mice results in growth, neurobehavioral, and hypomyelination phenotypes, reflecting a subset of clinical features of Pol III-related leukodystrophy patients. Myelination defects in the mice identify neural-specific roles for Pol III transcription. The phenotypes of Pol III-related leukodystrophic mice enable genetic and pharmacological approaches aimed at mitigating the consequences of this disease in humans.
Inequality in mortality between Black and White Americans by age, place, and cause and in comparison to Europe, 1990 to 2018
Authors: Schwandt Hannes , Currie Janet , Bär Marlies , Banks James , Bertoli Paola , Bütikofer Aline , Cattan Sarah , Chao Beatrice Zong-Ying , Costa Claudia , González Libertad , Grembi Veronica , Huttunen Kristiina , Karadakic René , Kraftman Lucy , Krutikova Sonya , Lombardi Stefano , Redler Peter , Riumallo-Herl Carlos , Rodríguez-González Ana , Salvanes Kjell G. , Santana Paula , Thuilliez Josselin , van Doorslaer Eddy , Van Ourti Tom , Winter Joachim K. , Wouterse Bram , Wuppermann Amelie
Published: September 2021

Significance

From 1990 to 2018, the Black–White American life expectancy gap fell 48.9% and mortality inequality decreased, although progress stalled after 2012 as life expectancy plateaued. Had improvements continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. Despite decreasing mortality inequality, income-based life expectancy gaps remain starker in the United States than in European countries. At the same time, European mortality improved strongly and even those U.S. populations with the longest life spans–White Americans living in the highest-income areas–experience higher mortality at all ages than Europeans in high-income areas in 2018. Hence, mortality rates of both Black and White Americans could fall much further in both high-income and low-income areas.
“How do you even know what ideophones mean?”
Authors: Nuckolls Janis B.
Published: September 2021

Using data from the Northern Pastaza (qvc) and Upper Napo Quichua (quw) dialects of Amazonian Ecuador, this paper argues that the semantics of ideophones, a highly marked form class of expressive words, is principled and describable with a combination of sensori-semantic features and a fine-grained typology of gestures, based on insights fromStreeck (2008)and others. Specifically, ideophones’ sensori-semantics are broken down into a semantic map consisting of 3 super- and 7 subcategorical distinctions. The greater the number of categories encoded by an ideophone’s semantics, the greater are the range of gestures used. Finally, gesture types identified byStreeck (2008)and others, were found among a very different group of people who are not western, educated, industrialized, rich, or democratic. Further research into ideophones and their gestures may find broader significance for ideophone semantics, and more generally, for the interrelations between language and gesture.
Dutch pragmatic markers in the left periphery
Authors: van der Wouden Ton , Foolen Ad
Published: September 2021

This chapter explores the left periphery of Dutch
utterances. Four positions hosting pragmatic markers (PMs) are
distinguished: the first sentence position (P1), a position
following P1 and two positions respectively preceding and following
a left dislocated constituent. We hypothesize that there are
correlations between these positions and pragmatic functions like
discourse coherence, subjectivity and intersubjectivity. A short
look is taken at asyndetic clusters of pragmatic markers in the left
periphery, we also assume functional motivations for the
linear ordering of PMs in the cluster. The goal of the chapter is
primarily descriptive, inspired by functionally oriented frameworks,
in particular Construction Grammar, Functional Discourse Grammar and
Interactional Linguistics. The illustrative data are mainly taken
from CGN, the corpus of spoken Dutch.
Interactions between distribution and functional uses in Italian
adversative pragmatic markers
Authors: Cimmino Doriana
Published: September 2021

This chapter describes the interaction between
distribution and functional uses of the Italian Adversative
Pragmatic Markers (APMs) ma and
però in spontaneous spoken language. These
forms are claimed to be distributionally and functionally
asymmetrical, as ma preferentially occurs in the
left periphery, performing a turn-taking function, while only
però can appear in the right periphery, with a
cohesive function. Results from a semasiological (form-to-function),
corpus-based and multi-level (prosodic, information and functional)
investigation show that APM asymmetry is not clear-cut. Although the
multi-level description supports Beeching and Detges’s (2014) function-periphery
asymmetry hypothesis as a general tendency, it also argues in favor
of a more fine-grained functional analysis.
Žinai ‘you know’ in Lithuanian discourse
Authors: Šinkūnienė Jolanta
Published: September 2021

This corpus-based study focuses on the frequency,
distribution patterns and functional profile of the pragmatic marker
žinai ‘you know’ in Lithuanian spoken discourse
and fiction. The data for the study comes from interviews,
spontaneous private conversations and a parallel corpus of English
and Lithuanian fiction texts. The results show that
žinai ‘you know’ can occupy clause initial,
medial and final positions, in which it can perform various
functions. They range from textual (indicating a word search or
hesitation, sustaining the flow of discourse, offering a
clarification, introducing information or arguments) to
interpersonal (making reference to common knowledge and seeking
understanding or agreement from the addressee).
Second person parentheticals of unintentional visual perception
in British English
Authors: Van Olmen Daniël
Published: September 2021

This chapter is the first systematic corpus-based
study of parenthetical see, you see and do
you see in British English. It compares (the
relationship between) their clause positions and their uses. The
results indicate, inter alia, that see is not
simply a shorter form of you see but also that some
conflation exists between the three markers. Furthermore, they
confirm some of the hypothesized associations of particular
functions with the left versus right clause periphery (e.g.
see’s attention-getting use in clause-initial
position) while challenging others (e.g. you see
able to mark clauses in both their left and right periphery as
explaining a previous one). The chapter also questions the notion of
(inter)subjectivity’s value in the debate about peripheries and
functions.
Extracting cosmological parameters from N-body simulations using machine learning techniques
Authors: Lazanu Andrei
Published: September 2021

We make use of snapshots taken from the Quijote suite of simulations, consisting of 2000 simulations where five cosmological parameters have been varied (Ωm, Ωb, h, n
s and σ8) in order to investigate the possibility of determining them using machine learning techniques. In particular, we show that convolutional neural networks can be employed to accurately extract Ω
m and σ
8 from the N-body simulations, and that these parameters can also be found from the non-linear matter power spectrum obtained from the same suite of simulations using both random forest regressors and deep neural networks. We show that the power spectrum provides competitive results in terms of accuracy compared to using the simulations and that we can also estimate the scalar spectral index n
s from the power spectrum, at a lower precision.
TCN-HBP: A Deep Learning Method for Identifying Hormone-Binding Proteins from Amino Acid Sequences Based on a Temporal Convolution Neural Network
Authors: Guo Jing
Published: September 2021

Hormone-binding proteins (HBPs) are carrier proteins that specifically bind to targeted hormones. Some evidence suggests that the abnormal expression of HBPs causes various diseases. Therefore, it is significant to accurately identify HBPs to study these diseases. Recently, many researchers have proposed traditional machine learning methods to complete this work, but these methods are neither suitable for training on large-scale datasets nor take into account the contextual features of HBPs. In this paper, I propose a new deep learning method, TCN-HBP, to distinguish HBPs. TCN-HBP consists of a coding layer, embedding layer, convolutional neural network (CNN) layer and temporal convolutional network (TCN) layer. The coding and embedding layers extend the protein sequences into two-dimensional matrix data. The CNN layer convolves the matrix data to form feature maps. The TCN layer captures the contextual features present in the feature maps. Experiments show that the data generalization capabilities and recognition accuracy (99.15%) of TCN-HBP on large datasets perform better than previous methods.
Detection of Sick Laying Hens by Infrared Thermal Imaging and Deep Learning
Authors: Li Pei , Lu Huishan , Wang Fujie , Zhao Shouyao , Wang Ning
Published: September 2021

The laying hens are prone to get sick during the growing period, and the temperature will fluctuate within a relative range when the disease occurs. This temperature change range can be used as a sign of pathological phenomena in the laying hens. In order to find the floating range of the body surface temperature of the laying hens raised in the poultry house in both healthy and pathological states, and the areas where there is a significant difference in the body surface temperature of the two, a detection method combining infrared thermal imaging technology and neural network is proposed. First, use an infrared thermal imager to obtain an infrared image of the body surface of a layer, and then use a convolutional neural network to establish a recognition model for the characteristic area of the layer, and extract the highest temperature of the region of interest in a healthy and pathological layer. Finally, analyse the temperature difference of each area of interest in the chicken body under these two conditions. The test results show that the accuracy of the convolutional neural network recognition model is 97%; the temperature fluctuation range of the three characteristic areas of healthy and pathological layers are different, and the maximum temperature difference area is 7.8°C.
A New Method for Geophysical Induced Polarization Inversion Based on Stochastic Medium Model and Sample-Compressed Artificial Neural Network
Authors: Liu Weiqiang , Yang Liangyong
Published: September 2021

Induced polarization (IP) is a near-surface geophysical exploration method. Inverting the electrical properties of the underground medium from surface apparent IP parameters is a highly nonlinear problem. To further improve the accuracy, the artificial neural network (ANN) algorithm is applied to the two-dimensional (2D) IP data inversion for the first time. We firstly produced smooth geo-electric models based on the stochastic medium theory, and obtained the corresponding theoretical responses through forward modelling. Then, we compressed the responses and models through image compression technology. Finally, the above compressed responses and models were used as input and output samples to train an optimal network system for inversion. We tested the algorithm with synthetic examples. The results show that ANN can improve the longitudinal resolution of the inversion results and make the inversion results more focused.
Artificial Intelligence (AI) Technology Assisted Emergency Management in Oil Industry
Authors: Wang Lei , Gao Shenghan , Chu Shengli , JiayiLi  , Jin Shuli , Li Na , Zhang Lianfang
Published: September 2021

Emergency management is considered to be a response to the risk of major accidents and disasters, while oil companies pay more attention to the post-emergency response and post-treatment, but do not care about the whole process of emergency management. Despite not necessarily receiving the most coverage, production safety accidents caused by unreasonable emergency management have become an urgent problem in petroleum industry. As the most advanced productive force in modern society, artificial intelligence is considered to lead the future, integrate into all aspects of today’s society, and even bring about industrial revolution. With the development of science and technology, artificial intelligence has been applied to all aspects of emergency management in petroleum industry, including intelligent prevention and emergency preparedness, monitoring and early warning, emergency response and rescue, post-recovery and reconstruction. The application of artificial intelligence can not only improve the level of emergency management, reduce the cost of labor expenditure, avoid casualties of emergency management personnel and field staff, but also improve the production efficiency of enterprises and maintain the safety of production in petroleum industry. The most important thing is that AI can involve the whole process of emergency management and bring industrial upgrading to the petroleum industry.
Meso-model Optimization of Composite Propellant Based on Hybrid Genetic Algorithm and Mass Spring System
Authors: Zhao Jiuling
Published: September 2021

The meso-structure of composite propellant directly affects its macroscopic properties. The primary premise of studying the macroscopic characteristics of composite propellant is to establish the meso-structure model which can reflect the actual formulation characteristics.In order to obtain the optimal composite propellant meso-structure model suitable for numerical analysis and calculation, the hybrid genetic algorithm was used to optimize the reconstructed meso-structure model. In order to avoid different degree of overlap between particles, the mass spring system was further improved. The resulting meso-structure model not only preserves the statistical characteristics of the propellant, but also meets the requirement of minimizing the optimal size. The reconstruction and optimization algorithm of the optimal meso-structure model are established in this paper, which has high theoretical significance and engineering application value for the prediction of mechanical properties of composite propellant.
Robust Unsupervised Feature Selection Based on Elastic Distance Loss
Authors: Pan Jinyan , Xie Youwei , Gao Yunlong , Gao Peng , Chen Baihua , Lin Xiangyujie
Published: September 2021

In recent years, it is a desirable way to introduce graph learning into feature selection, and it has achieved good performance in feature selection tasks. But three issues need to be concerned: (1) how to learn the similarity of samples during graph construction adaptively; (2) the performance of feature selection heavily depending on the construction of the graph; (3) most of the feature selection algorithms all use L2,1-norm for feature selection, which is not suitable for all data distributions. In this paper, we propose a robust feature selection framework to solve the above problems, which incorporated data reconstruction, graph embedding, and feature selection into a uniform framework. We use the probability of the neighbors to reconstruct the original data adaptively. Then, a novel adaptive loss function, namely, the elastic distance loss function is proposed. Finally, we compared seven state-of-art unsupervised feature selection algorithms in several benchmark datasets, and the experimental results proved the effectiveness of our proposed model.
Dynamic Optimization Algorithm Based on Multi-modal Niche Lion Swarm by Sensitive Individuals
Authors: Zhang Qi , Jiang Mingyan
Published: September 2021

Aiming at the problem that the model of complex dynamic system which is difficult to track its global optimal solution, this paper proposes a multi-modal niche lion swarm optimization algorithm based on sensitive individuals to solve the optimization problem of complex dynamic system. Sensitive individuals are set in the lion swarm algorithm to perceive changes in the dynamic environment, and to track the global optimal value in time. It combines with niche technology to increase the diversity of the population and avoids falling into local extremes. The dynamic environment is simulated by the dynamic function generator and compared with other optimization algorithm to verify the superiority of the algorithm proposed in this paper.
An Overview of Video Super-Resolution Algorithms
Authors: Liu Chenming , Gang Ruipeng , Li Jinjing , Fang Ji , Yu Haodong
Published: September 2021

We investigate some excellent algorithms in the field of video space super-resolution based on artificial intelligence, structurally analyze the network structure of the algorithm and the commonly used loss functions. We also analyze the characteristics of algorithms in the new field of video space-time super-resolution. This work helps researchers to deeply understand the video super-resolution technology based on artificial intelligence.
Research on H
∞ Preview Control Algorithm for Industrial Wireless Sensor Networks
Authors: Shi Yuanbo , Huang Yueyang , Hou Shaojing , Wu Yinghao
Published: September 2021

In order to solve the problem of wireless sensor network control system with network delay and packet loss, a H
∞ preview control algorithm is designed. Firstly, the wireless sensor network model with delay and packet loss is established, and the system error and predictable target signal are introduced to construct the extended error system. Secondly, the state feedback controller with memory is designed. By constructing Lyapunov function and linear matrix inequality, the design method of H
∞ controller and the sufficient conditions for the stability of the system are derived. The optimal H
∞ preview controller algorithm is obtained by solving the LMI optimization problem. Finally, the effectiveness of H
∞ preview controller algorithm is verified by simulation.
A Novel Steganography Scheme for Color Image Based on HLS Translation
Authors: Shao Guoqiang , Jie Longmei , Shen Dan
Published: September 2021

In recent years, steganography has attracted extensive attention, but most of steganography schemes are aimed at grayscale images. Therefore, a novel steganography scheme for color image based on HLS translation is proposed in this paper. Firstly, the color cover image is decomposed from RGB three channels to HLS three channels. Then the image of H channel is selected as the cover image for embedding secret information due to its texture feature of original image. The universal distortion function UNIWARD is utilized to embed the secret information into the image of H channel. Finally, the steg image transmitted in common channel is obtained by inverse HLS transform using the single channel image embedding the secret information. The extensive experimental results indicate that our scheme has high security and can also resist the detection of steganalysis schemes based on CNN.
GSW: A High Performance IQA Index Based on Global and Saliency Window Similarity
Authors: Fan Yibo , Meng Zihao
Published: September 2021

Perceptual image quality assessment (IQA) attracts significant attention in recent years. It is proved that both global score and an image’s visual saliency (VS) are consistent with subjective evaluation. The global quality score reflects the consistency of the overall structure between two images, and VS map contributes complementarily in evaluating perceptual quality. This paper presents an effective IQA index based on global and saliency window similarity, namely GSW. It chooses VS map as an image feature and uses a special strategy to draw the saliency window with largest significancy. Meanwhile, the background area is taken into account to guarantee the robustness of the quality score. Experimental results on four most widely used databases verify that, compared with state-of-the-art IQA methods, GSW performs consistently well can provide more accurate quality prediction with a low computational complexity.
Research on Unbalanced Sample Segmentation of Remote Sensing Image
Authors: Li Yanping , Wang Lu , Zhang Lei , Wang Shiying , Chen Haiwen , Zhu Xiaolan
Published: September 2021

This article proposes a framework for the unbalanced sample segmentation of remote sensing images on an open data set. For the few sample categories, improved by converting it into binary segmentation and combining with weighted cross-entropy loss, and then merged with the segmentation result of the sufficient sample categories. Finally, the mIoU (mean Intersection of Union) of the 8 categories is increased by 4.5% compared to the results before the improvement, especially, the results of the few sample category road and grassland are increased by 10.2% and 9.7%. The experiments show that the framework can greatly improve the segmentation performance of the few sample categories, and have a good guiding significance for the problem of multiclass unbalanced sample segmentation.
Research on Security Protection Technology of Digital Library System in the Era of Equal Protection 2.0
Authors: Li Zhijie
Published: September 2021

New Coronavirus pneumonia is eroding the world, and digital libraries are even more important. How to control the network security of digital library system? According to the requirements of equal protection 2.0, this paper analyzes the security requirements of digital library network, and puts forward the security protection technology of digital library system under equal protection 2.0 system from the four perspectives of secure communication network, secure area boundary, secure computing environment and security management center. Based on the security protection technology framework of equal protection 2.0, this paper studies the security evaluation method of digital library, and puts forward the security protection technology solution.
Research on the Relationship between Engine Drag Torque and Cylinder Compression Pressure Based on Regression Analysis
Authors: Kang Hao , Zhou Min
Published: September 2021

This paper first proposes that cylinder tightness is an important factor affecting engine performance, which can directly reflect engine technical conditions. Cylinder tightness directly affects cylinder compression pressure, and cylinder compression pressure directly affects engine drag torque. Then, based on the test of real engine, the formula of the relation between the drag torque and the compression pressure is obtained by using the method of linear regression analysis, which provides a real and effective new method and means for inspecting the cylinder sealing. Data is obtained by preliminary analysis was carried out on the data of the basic characteristics, contact, and then use regression model to establish correlation between variables, with the method of mathematical model to describe the relation between resistance torque and compression pressure, through the relationship to provide scientific and effective in sealing cylinder detection method, make forecasting data more real and effective, More guidance for cylinder maintenance and state detection.
Application Research on Extreme Learning Machine in Rapid Detection of Tool Wear in Machine Tools
Authors: Wu Q , Liu E , He Y H , Tang X
Published: September 2021

In order to put an end to the product quality accidents caused by cutting tool breakage or severe wear in machining process, the paper explored an ELM model detection method based on voice recognition. In this paper, firstly it analysed the features of cutting sound signal in time-frequency domain, then discussed the extraction method of tool working state sensitive spectral energy statistical feature based on wavelet packet decomposition, and finally constructed an ELM fast detection model based on sound feature recognition. The experimental results demonstrated that the ELM detection model could achieve higher detection accuracy and faster response time. The simulation results show that the ELM model is effective and applicable in detecting tool wear with the help of sound recognition.
Improving Cross-Project Defect Prediction with Weighted Software Modules via Transfer Learning
Authors: Chen Yizhou , Dai Heng
Published: September 2021

Cross-project defect prediction is investigated to resolve the trouble that software program defect prediction besides historic data. However, there are differences in distribution of software metrics of different software projects, which decreases the overall performance of cross-project defect prediction. This research presents a transfer learning-based cross-project fault prediction approach. The weights of the training software modules are determined by analogy with gravity and compared to those in the test set. The costs associated with different prediction errors are considered. Cost-sensitive C4.5 is employed on weighted training data for cross-project defect prediction. 10 projects from NASA are used in our experiments. Our suggested technique delivers promising cross-project defect prediction results, according to the results, 0.81, 0.41 and 0.8 in average PD value, F-measure value and AUC value, which are best compared to Naïve Bayes based cross-project defect prediction.
3D Indoor Scene Completion via Room Layout Estimation
Authors: Xia Wei , Lu Rongfeng , Sun Yaoqi , Xu Chenghao , Lv Kun , Jia Yanwei , Zhu Zunjie , Zheng Bolun
Published: September 2021

Recent advances in 3D reconstructions have shown impressive progress in 3D indoor scene reconstruction, enabling automatic scene modeling; however, holes in the 3D scans hinder the further usage of the reconstructed models. Thus, we propose the task of layout-based hole filling for the incomplete indoor scene scans: from the mesh of a scene model, we estimate the scene layout by detecting the principal planes of a scene and leverage the layout as the prior for the accurate completion of planar regions. Experiments show that guiding scene model completion through the scene layout prior significantly outperforms the alternative approach to the task of scene model completion.
Research on Dual-Mode Communication Technology Based on Power Line Carrier and Micro Power Wireless
Authors: Long Yan , Chen Yongli , Zhang Xudong , Xiao Deyong , Li Zheng , Tang Xiaoke
Published: September 2021

At present, the power meter reading system mainly uses the single power line carrier meter reading mode or the single micro power wireless meter reading mode. Due to the disadvantages of the two modes, the single meter reading mode can not meet the meter reading under different environmental conditions. In order to improve the success rate of communication, this paper puts forward the dual-mode communication technology of power line carrier and micro power wireless integration, which is based on the power line carrier It overcomes the defects of single meter reading mode and improves the real-time performance, reliability and success rate of meter reading.
Research on Role Access Control Model Based on Identity Authentication
Authors: Chen Ling
Published: September 2021

Cryptography and access control are the core technologies for a secure operating system. Cryptography can guarantee the confidentiality, integrity, availability and unforgeability of information in the access control system. In the identity-based cryptosystem, the user’s private key is centrally generated by the key distribution center, and key escrow is a major security risk. In view of this problem, it is proposed that multiple trusted entities participate in the key distribution scheme in a serial manner. At the same time, this paper adds a separate blind factor to each user to increase security of the scheme; it also introduces the concept of virtual key, which uses additivity of the key space in the pair-based encryption scheme. In key generation, a timestamp T is added, which enables one-time pad of the system, enhances security of the system, and eliminates collusion attacks by KGC and multiple KPA. Finally, the improved signcryption scheme is combined with the RBAC model, and the I_RBAC model is proposed, which enables identity authentication and information confidentiality of users in simple communication in the RBAC model. Finally, the efficiency and safety of this scheme are analyzed.
A Software Defined Network Scheme for Intra Datacenter Network Based on Fat-Tree Topology
Authors: Hu Siquan , Wang Xinyu , Shi Zhiguo
Published: September 2021

Nowadays datacenters face a big challenge, because the development of cloud services requests a large amount of capital input, high maintenance skills and cost. The major disadvantages of current datacenter network include the high cost of equipment and maintenance, QoS, failure recovery time, network virtualization etc. In this paper, we proposed a software defined datacenter network. The programmable controller is responsible for the management of the traffic scheduling including topology discovery, routing and Quality of Service. The SDN is based on Fat-tree network architecture and max-min fairness. A Genetic Algorithm optimized Radial Basis Function neural network is used to compute the service weight for maximizing the utilization of network resource. An experiment of the network bearing different kinds of services based on Openflow is described. This well-designed fat-tree network has high efficiency in traffic distribution, and has integrated the traditional network architecture and new SDN technology.
Research on Overload Signal of New Impact Body Based on Air Cannon Test and Simulation
Authors: Tang Tong , Ma Shaojie , Li Feiyin , Wei Jian , Shi Huifa , Zhang An
Published: September 2021

Air cannon simulation test method is a common method to generate high overload signal. In this paper, a new impact body model for air gun test is proposed. Based on the model, the impact dynamic theory is analysed, and the variation law of high overload signal in accelerometer due to multiple reflection and transmission of stress wave in the impact process is studied. The finite element model is established by using ANSYS / LS-DYNA software to simulate and analyse the impact process, and a test platform is built to verify the simulation. The test results and simulation results show that the impact body can generate a “W” shape high overload signal during the impact process, which also verifies the rationality of the theoretical analysis. The methods and conclusions of this paper have certain significance for the study of the new type of impact body and the high overload signal produced by the impact test.
Development of Tailings Pond Flood Routing Simulation System Based on LabVIEW
Authors: Cui Yiyuan , Mei Guodong , Wang Yali , Wang Shan
Published: September 2021

Flood routing is an important work for tailings ponds to flood control. Although the flood routing method is relatively mature, the manual calculation and parameter selection still remain a major challenge for field engineers. In this study, a program, developed by LabVIEW, is introduced to improve the tailings ponds flood routing calculation. The developed program provides two flood generation calculation methods and four kinds of flood discharge model, which can be applied to any tailings pond and achieves flood routing fast and accurately. An application of Dexing 4# tailings pond is conducted to verify the function of program. The result indicates that the program shows good performance on calculation speed and accuracy.
Application of modeling and analysis technology of mechatronics system in mechanical engineering
Authors: Wang Dawei
Published: September 2021

In the context of the rapid development of the global economy, different enterprises in the process of development, will be fully applied to various economic order, which improves the comprehensive competitiveness of enterprises. The innovative application of mechatronics system in mechanical engineering industry can promote the modernization and information development of mechanical engineering industry to a certain extent. In this process, we need to ensure the efficiency and reliability of mechanical design, so as to solve various problems existing in the design of the current mechanical system and electronic system. At present, in the development process of mechanical engineering, to fully apply the modeling and analysis technology of mechatronics system, it is necessary to understand the corresponding application principles, build the modeling and simulation application platform of mechatronics system, and carry out the joint simulation analysis of mechatronics products. Only in this way can we effectively solve various problems existing in the process of electromechanical operation of the model and ensure the design level of mechanical engineering.
Kinematic and Dynamic Characteristics in a Crank-rocker Four-bar Linkage
Authors: Chen Shutong , Shen Xiushi , Ye Chuwei
Published: September 2021

Planar four-bar linkage is widely used in mechanical engineering. The degree of freedom of the linkage is one, and different organizations of the lengths of the four bars could distinguish it in several different types. The one is the crank-rocker mechanism. The parameters decided by the lengths of the bars are the wiping angle, transmission angle, and the quick-return ratio, which were analyzed in this report. Then the three-dimensional model and the physical model were built. In addition, the kinematic characteristics of the prototype were deduced by simulation, and some experimental works researched dynamic characteristics. Finally, the conclusions about the linkage were made.
The investigation of stability enhancement within a two-stage compressor utilizing the non-asymmetric stator
Authors: Zhao Jiayi , Yang Dangguo , Lu Qingfei
Published: September 2021

As the compressor plays a key role in the marine-used gas turbine, its stability determines the operation condition of the power engine of the ship. The paper investigates the performance improvement of the compressor by utilizing a new-designed asymmetric stator. The results show that the flow distortion upstream is significantly constrained by the developed stator and the unsteadiness of the static pressure coefficient and Mach number at R2 inlet decrease by 74% and 48% respectively.
Research on Redundant Design Technique for USV Autonomous Control System
Authors: Huang Wenbin , Xu Hao , Feng Jiaxiang , Wang Lifeng
Published: September 2021

In the field of USV autonomous control system design, redundant design technology is the important method to improve system reliability. In order to solve the problem of insufficient reliability when USV carrying out long endurance and open sea task, this paper analyzes the critical design elements of autonomous control system redundant configuration, presents a high reliable hybrid redundant structure for USV autonomous control system, and realizes redundant strategy and fault-tolerant control. This paper forms the USV autonomous control system redundant configuration scheme comply with the fault-tolerant capability and redundant rank of USV autonomous control system. Redundancy management strategies and algorithms are used to implement USV autonomous control based on hybrid redundant design. The reliability analysis and computation validate task reliability of the autonomous control system based on hybrid redundant structure.
Fluid-structure interaction Simulation for Hydro-elastic Performance of marine Propeller at Full-Scale
Authors: Qian Zhipeng , Ji Nan , Yang Guang , Shu Linzhao
Published: September 2021

In this study, CFD-FEM bi-directional fluid structure interaction (FSI) methodology using STAR-CCM+ is adapted for the hydro-elastic interaction simulation of the propeller at full-scale. To validate the FSI simulation reliabilities, the open-water curve of the rigid and NAB propellers VP1304 at model scale are computed. Then, the propeller KP505 is employed for the open-water test to study scale effect and hydro-elastic performance. The change of thrust coefficient, torque coefficient, efficiency, stress distribution, deformation are presented. From the results, the hydrodynamic difference due to scale effect and hydro-elastic performance are observed. Analysis of structural response of NAB propeller shows that scale effect plays a role.
Experimental study on enhanced heat transfer tubes in falling film evaporation
Authors: Zhang Zhao , Wang Xuesheng , Chen Qinzhu , Zhang Ting
Published: September 2021

The vertical tube falling film evaporation experimental platform was built, and the falling film evaporation heat transfer experiment was carried out. Comparative study was carried out between two types of enhanced heat transfer tubes, which are converging-diverging tube and the transversally corrugated tube, to explore their heat transfer characteristics of falling film evaporation. The results show that the falling film evaporative heat transfer coefficient of the two tubes increases with the increase of the unit peripheral flow rate, the heat transfer temperature difference, heat flux and the Reynolds number of the flash steam. The falling film evaporation heat transfer coefficient of the converging-diverging tube is about 1.09 times that of the transversally corrugated tube. According to the experimental data, the falling film evaporation heat transfer correlations of these two types of tubes were obtained. These results provide a useful reference for the using of transversally corrugated tube and converging-diverging tube in vertical falling film evaporator.
Control Circuit design of permanent magnet synchronous motor control system based on DSP
Authors: Sun Zhangjun , Ren Wu , Liu Le , Duan Chao , Li Lin
Published: September 2021

This paper introduces the design and implementation of hardware circuit of permanent magnet synchronous motor Servo Controller Based on DSP.In this scheme,TMS320F28335 is used as the control core, and drv8312 is used as the three-phase motor driver chip. The main control circuit, communication circuit, drive circuit, current feedback circuit and protection circuit are designed in detail. The reliability of the control circuit is verified by experiments, and the servo control of PMSM is realized.