bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of the Convective Stratification of Airflows in a Mine Shaft
Authors: Kolesov E V , Kazakov B P , Grishin E L
Published: June 2021

The experimental study of heat and mass transfer in the atmosphere of a skip shaft of a Gypsum mine was carried out during the summer and winter seasons. The air flow overturning was observed in the winter season due to the ingress of cold heavy air from the surface into the shaft space. To analyze this phenomenon, a computational fluid dynamics (CFD) model of heat and mass transfer processes in a mine shaft was developed, considering the vertical temperature gradient, roughness of the shaft walls, heat exchange with the shaft lining. Based on numerical simulation, it was found that at relatively low air velocities in the shaft and with a relatively large difference between warm air in the shaft and cold air on the surface, the latter begins to penetrate the shaft and descend down it, gradually filling its space. The interaction of cold air from the surface with the warm air rising up the shaft, as well as with warm walls of the shaft leads to the formation of an unsteady convective vortex cellular structure along the shaft. The depth of the vortex depends on the velocity of the air in the shaft, as well as the difference between the temperatures of the warm and cold air. Based on the obtained numerical simulation data, it was possible to calculate the minimum allowable air velocity at which partial return air flows appear in the shaft cross-section.
Stationary Thermomagnetic Convection of Ferrofluid in an Enclosed Loop
Authors: Koskov M A , Pshenichnikov A F
Published: June 2021

This paper presents an experimental study of thermal convection of ferrofluid inside a closed hydrodynamic loop heated from the side in the presence of a magnetic field applied to the loop section nearby the heater. The pipes of the circuit are blown with a stream of thermostatic air, which ensures a constant heat transfer coefficient on the outer surface of the pipes and an exponential temperature distribution along the circuit. The value of the exponent measured provide information on the integral axial heat flux (Nusselt number). The experiments were conducted with undecane under natural gravitational convection and with a colloidal solution of magnetite in kerosene of moderate concentration under mixed (gravitational and thermomagnetic) convection at the Rayleigh numbers varied in the range 103 – 104. It is shown that thermomagnetic convection causes a 4 – 6 – fold increase in heat transfer.
New Experimental Results on Steady Streaming in Oscillating Deformable Spherical Container
Authors: Kozlov N V
Published: June 2021

The paper presents an experimental study of steady streaming generated by harmonic oscillations of the boundaries of a deformable spherical container. The container is filled with a viscous fluid and its oscillations are produced by means of two linear servo motors, installed symmetrically. The shape of the boundary during deformation is studied by processing images recorded with a high speed camera. The flows are investigated using the particle image velocimetry. In the analysis of results, the focus is made on the relation between the shape of the oscillating boundary, the dimensionless frequency and the streaming velocity. The possibility of controlling the steady streaming pattern in order to affect the convective mass transfer is discussed.
Mathematical Modeling of Invasive Carcinoma: Biomechanics of Small Groups of Cancer Cells
Authors: Krasnyakov I V , Bratsun D A , Pismen L M
Published: June 2021

According to the latest research, cancer is a complex biological system that evolves over time and space. This means that cancer cells differ from each other in their functions in the tumor. They engage in various interactions with the microenvironment and compete for available nutrients to survive. The main problem of mathematical modeling in oncology today is the heterogeneity of a typical malignant neoplasm. In this work, we propose a chemomechanical model of the pattern formation of small groups of cancer cells of invasive carcinoma of a non-special type (IC NST). The model assumes that carcinoma is a heterogeneous formation, which consists of cells of different phenotypes performing different tasks to maintain the existence of the tumor. In the model, each cell is represented as a deformable polygon that changes its shape and size as the tissue develops. Numerical modeling implements various subtypes of IC NST structures. These patterns are compared with morphological structures identified in clinical studies.
Dynamics of Flat Barium Hexaferrite Particles in a Lyotropic Liquid Crystal
Authors: Lebedev A V , Lysenko S N
Published: June 2021

This paper describes the results of experiments on the magnetization of barium hexaferrite particles embedded in lyotropic liquid crystals. The carrier liquid crystal medium was an aqueous solution of a mixture of sodium lauryl sulfate and lauric acid in a ratio 2/1. Barium hexaferrite particles were stabilized with two layers of surfactant. The first layer consisted of oleic acid molecules. Second layer was a mix of sodium lauryl sulfate and lauric acid in a ratio 1/1. The process of particle magnetization was investigated by observing the effect of birefringence. The intensity of light passing through the system of crossed polaroids and the time of its establishment were measured depending on the magnitude of the magnetic field and the concentration of the components of the liquid crystal. It was found that the field dependence of the birefringence effect changes significantly depending on the concentration of the liquid crystal. In a concentrated solution in the liquid-crystalline phase, a significant enhancement of the birefringence effect is observed in weak fields. As the concentration of the solution decreases, the field dependence of the birefringence effect smoothly transforms into the curve for particles dispersed in water.
Behaviour of a Ternary Mixture with the Net Separation Ratio Close to Zero
Authors: Lyubimova Tatyana , Prokopev Sergei , Shevtsova Valentina
Published: June 2021

The behaviour of the ternary hydrocarbon mixture of toluene-methanol-cyclohexane in mass proportion 0.62/0.31/0.07 is studied. The direct numerical simulation is carried out for the two-dimensional closed cavity heated from above. The mixture is supposed to be in the gravity field. The behavior of the mixture is predominantly caused by the Soret effect (thermal diffusion). An important parameter, responsible for the Soret effect, is the net separation ratio, Ψ. For the mixture under consideration, the two sets of values of Ψ are known. In both cases, the values of Ψ turn out to be close to zero, but in one case Ψ is slightly positive, and it is slightly negative in the second one. This results in qualitative difference in the evolution of the mixture under consideration. If Ψ > 0, the mixture comes to the mechanical equilibrium. If Ψ < 0, we observe the system to be at the border of stability, under small perturbation there is no instability, but for the perturbation amplitude higher than a threshold value of the convective single-vortex flow arises.
Convection of Viscoplastic Fluid in Square Cavity Heated from the Sidewalls
Authors: Lyubimova T P , Kazimardanov M G
Published: June 2021

The paper is devoted to the numerical study of two-dimensional convective motion of a viscoplastic fluid in a closed region under lateral heating. The problem is solved numerically using the ANSYS Fluent software. The Bulkeley-Herschel model describing viscoplastic behavior was chosen as a non-Newtonian fluid model. Under certain rheological parameters, this model is reduced to a Newtonian fluid model, the behavior of which is also investigated as a limit case. Based on the results of the calculations, the dependence of the maximum value of the stream function in the cavity on the Rayleigh number is plotted and the evolution of the unyielded zones with an increase in the Rayleigh number is traced. The threshold value of the Rayleigh number, at which a sharp growth of the flow intensity is observed, has been determined. The calculated threshold value of the Rayleigh number for the Bulkley-Herschel liquid was found to be very close to the threshold value of the Rayleigh number at which the flow of the Bingham liquid arises, which was obtained analytically.
Convection of a Binary Mixture with Thermal Diffusion Coefficient That Depends on Temperature
Authors: Lyubimova T P , Rushinskaya K S , Zubova N A
Published: June 2021

In this paper we present the results of numerical simulation of nonlinear regimes of a NaCl aqueous solution in a square cavity with rigid and impermeable for substance boundaries. The vertical boundaries are thermally insulated, there are different constant temperatures on horizontal ones, it corresponds to the heat from below. The calculations are carried out within the non-stationary approach, with using of Boussinesq approximation and taking into account the polynomial dependence of the thermal diffusion coefficient on temperature. According to experimental data, the sign of thermal diffusion coefficient of the mixture under study changes at a temperature 285.4 K. In this work we consider a temperature range such that the sign of the thermal diffusion coefficient changes inside the simulated region. Other transport coefficients factors are considered as constant. The calculations were carried out for the cases of Earth and reduced gravity. A comparison is made with the case of the thermal diffusion coefficient constant value, which is negative at the considered average temperature.
Numerical Modeling the Effect of Static Indentation on the Rate and the Fatigue Crack Growth Trajectory
Authors: Matvienko Yu G , Razumovskii I A , Fedorov A A
Published: June 2021

The results of numerical modeling (in ANSYS) are presented, concerning the effect of the local residual stress field in the vicinity of the crack tip on the fatigue crack growth rate and change of the crack trajectory. Static indentation by a spherical indenter is considered as a method for creating a residual stress field. In this case, the point (or points) of indentation can be located both symmetrically relative to the line of initial crack orientation and with an offset. It is shown that the fatigue crack can grow in the direction opposite to its initial orientation. This effect can be employed to control the fatigue crack growth trajectory.
Analytical and Numerical Study of Biaxial Bending on VHCF Testing Machine
Authors: Nikitin A D , Stratula B A
Published: June 2021

Modern VHCF testing regimes are studied. A new loading scheme applicable to a piezoelectric fatigue testing machine is proposed. The scheme is studied analytically and numerically. The analytical part comprises the calculation of the specimen’s geometry to operate correctly on the VHCF testing machine, as well as the specimen’s stress-strain state calculation during an experiment in order to determine the one’s durability. A model based on a kinetic damage equation is introduced. This model is used in the numerical experiment. The behavior of a finite-element specimen in a fatigue experiment is calculated from the beginning up to the stage of active crack growth.
Study of Heat and Mass Transfer in Ventilation Shafts of Deep Mines in the Case of Airflow Reverse
Authors: Olkhovskiy D V , Kuzminykh E G , Zaitsev A V , Semin M A
Published: June 2021

This article presents the results of a simulation of conjugate heat transfer between cold air and warm shaft lining during airflow reverse at a hard rock mine. A comparison of the numerical results with collected experimental data was carried out. A significant discrepancy between the two was revealed, indicating that not all heat sources and additional air heating mechanisms were taken into account in the simulation. Possible reasons for the discrepancy are discussed and the most probable reasons are identified for further study. A quantitative assessment of the possible factors considered is carried out. Further tasks for research are determined.
Influence of a Liquid on the Deformation Behavior of Porous Nickel and Titanium under Compression
Authors: Panfilov Gleb P , Zaytsev Dmitry , Panfilov Peter , Kiseev Valery
Published: June 2021

The deformation behavior of capillary porous (CP) Ni and CP Ti is examined under uniaxial compression in air, water, and ethanol. CP metals contained inert liquids such as H20 and C2H5OH are used as the heat pipes’ active elements in space applications. The samples for mechanical testing were isostatic compacting and vacuum annealing (porosity of 60%). Uniaxial compression tests were carried out in the air, water, and ethanol in Shimadzu AG-50K XD (traverse rate 0.1 mm/min). It was shown that CP Ni and CP Ti exhibit the ductile deformation behavior in all cases, which is inherent to Ni and Ti. The ethanol environment induces the increase of the compression strength and the total deformation in both materials compared to deformation behavior in air and water. Therefore, a heat pipe’s failure containing CP Ni and CP Ti matrixes and ethanol as the working body is caused rather by manufacturing defects, but not the structural materials’ intrinsic properties.
Four approaches for description of stochastic systems with small and finite inertia
Authors: Permyakova E V , Klimenko L S , Tyulkina I V , Goldobin D S
Published: June 2021

We analyse for approaches to elimination of a fast variable, which are applicable for systems like passive Brownian particles: (i) moment formalism, (ii) corresponding cumulant formalism, (iii) Hermite function basis, (iv) formal ‘cumulants’ for the Hermit function basis. The accuracy and its strong order are assessed. The applicability and performance of two first approaches are also demonstrated for active Brownian particles.
Dynamics of Magnetic Fluid Cylinder in Inhomogeneous Magnetic Field
Authors: Shel’deshova E V , Polunin V M , Churaev A A , Ryapolov P A
Published: June 2021

The dynamics of some magnetic fluid (MF) samples of various concentrations filling the tube horizontally and held by a field of a magnetic axial system made based on unipolar permanent rare-earth ring magnets were studied. The magnetic field of an “axial” magnetic system of MSO was studied, as well as the dependence of the system oscillation frequency on the length of the MF cylinder. An original method for determining MF magnetization is proposed and applied to the obtained data. Magnetization was determined for three magnetic fluid samples. The results obtained by the developed method are comparable to the magnetization values obtained by the ballistic method. The developed and presented technique of a dynamic experiment with measuring oscillations frequency of the “MF column suspended in a strong and inhomogeneous magnetic field” system involves the creation of a new absolute method for determining saturation magnetization and can be useful for studying magnetophoresis and aggregation processes of magnetic nanoparticles. This technique is used to study the degree of elastomagnetic consistency parameters over time.
Forecast of the Surface Tilt Based on the Monitoring Data of Settlement of a Group of Buildings
Authors: Tsvetkov R V , Glot I O , Epin V V , Shardakov I N , Shestakov A P
Published: June 2021

This paper presents the results of long-term monitoring of ground subsidence above flooded mining. To assess the change in the shape of ground surface, the data obtained by monitoring the settlement of the foundation of a large group of buildings were used. The control of the slope was carried out using automated hydrostatic level systems mounted on the foundations of 40 buildings located in this area. The accumulated data on the long-term evolution of the tilt were processed using the methods of statistical analysis of non-stationary time series. Choice of forecast model was made based on a comparison of forecast and real monitoring data. A forecast based on 5-year monitoring data predicts that the observed deformation processes in the rock massif will not change over the next 2 years.
Experimental Study of Steady Flows in Centrifuged Immiscible Liquids in Rotating Horizontal Cylinder
Authors: Vlasova O A , Karpunin I E , Kozlov N V
Published: June 2021

The steady time-averaged flows in a rotating system of immiscible fluids are studied experimentally. The fluids fill a horizontal cylindrical container and are brought into a centrifuged state, when a less dense fluid forms a cylindrical core, and a denser fluid is distributed in the form of a coaxial layer. Under the action of the gravity field, the core is steadily displaced along the radius in such a way that its axis is oriented parallel to the container axis and remains stationary in the laboratory frame of reference. In the frame rotating with the container, the core and the fluid surrounding it oscillate. This leads to the generation of a steady flow in the form of differential rotation of the fluid with respect to the container. To study the structure of the flow, light-scattering tracers of neutral buoyancy are added to the liquid. The flow rate is calculated from their displacement. Measurements show that at the interface, from the side of the external fluid, a Stokes boundary layer is formed, at the boundaries of which a tangential discontinuity of the averaged velocity is formed.
Approximation of Heat Dissipation-Crack Rate Curve for Fatigue Crack in Stainless Steel
Authors: Vshivkov A , Iziumova A , Prokhorov A , Mybassarova V , Plekhov O
Published: June 2021

The experimental and theoretical analysis of thermodynamical peculiarities of heat flux at the fatigue crack tip during its propagation was made in presented work. The goal is to elucidate the relation between heat flow at the crack tip and kinetic of fatigue crack propagation for different loading conditions. The plane specimens with notch made from stainless steel (AISI 304) were studied. There were two types of specimens for uniaxial loading and one type for biaxial loading. A heat dissipation during fatigue crack propagation was measured by simultaneous use of contact and noncontact techniques. The samples were subject to cyclic loading with constant stress amplitude and different biaxial coefficients. The functional dependence between crack propagation and heat flow at the crack tip was received by experiment measurement and analytical calculation. This relation depends on only type of material and righty for all fracture mode.
Research of Ionic, Molecular and Cellular Mechanisms for Formation of Electric Impedance in Biological Fluids and Tissues
Authors: Zuev A L , Shakirov N N , Sudakov A I , Ju Mishlanov V
Published: June 2021

Contemporary medicine applies the analysis of molecular composition and physicochemical properties of biological fluids as one of the main tools for diagnostics and control over body state and behaviour of pathological processes. However, most laboratory diagnostics methods (such as biochemical, enzyme-linked immunosorbent assay, etc.) are too expensive and time-consuming. They demand the availability of well-equipped laboratories, complex equipment, scarce and expensive reactants and materials and the highly skilled medical staff. Compared to them, bioimpedansometry is an incomparably simpler and cheaper method of laboratory research, becoming increasingly popular for diagnosing internal diseases. In the current research the main physical factors responsible for bioelectrical impedance variations in some conductive intracellular and extracellular biological fluids with different protein molecules, cell components and microbes were studied experimentally. The original laboratory impedance meter was developed for investigation of blood or interstitial biological fluids as well as condensates composition in orderto determine the concentration of organic substances in them and the rate of biochemical and immune reactions.
Features of modeling multiphase media in problems of electromagnetic generation of flows
Authors: Kolesnichenko I , Losev G , Eltishchev V , Mamykin A
Published: June 2021

The study of the electromagnetic force acting on a medium with inhomogeneous electrical conductivity has been carried out. The electrical conductivity changes abruptly which simulates the liquid–solid interface during the crystallization of a pure metal. The electromagnetic force is created by a traveling field inductor with one of the most demanded in metallurgy construction. The results showed a significant dependence of the electromagnetic force on the position of the interface with respect to the inductor. Consequently in the mathematical modeling of the directional crystallization process under the influence of an electromagnetic force created by an inductor of this type it is necessary during the movement of the interface, either to do the calculation of the electrodynamic part of the problem anew or to use the method of canonical domains.
3D Instability of a Toroidal Flow in the Liquid Partially Covered by a Solid Film
Authors: Demin V A , Petukhov M I , Shmyrova A I
Published: June 2021

The structure of a steady radial thermocapillary flow from the local heat source in cylindrical geometry has been studied numerically. The up boundary of the liquid was partially covered by the stationary film of an insoluble surfactant, pushed to the wall of the cavity. The calculations are fulfilled on the base of interfacial hydrodynamics equations by using mathematical package “Comsol Multiphysics”. It is shown that the effect of a radial flow symmetry breakdown appears as a result of convective instability, so that the initial poloidal rotation of the liquid transforms into the azimuthal plane. The system of inclined steady volumetric vortices is formed under the film of surfactant. The inclination angle of the plane of rotation in dependence on the intensity of radial thermocapillary flow is studied. It is shown that the azimuthal vorticity can be regulated by the power of point-heat source and by free surface area. The increase of heating intensity leads to the growth of the azimuthal vorticity. Thus, the initially radially symmetric toroidal flow is divided into two parts with the origination of vortices in the azimuthal plane under the film.
Application of Diagram Image Classification Based on PCBMER
Authors: Wang Ruixiang
Published: June 2021

Nowadays, in order to express data more clearly and accurately, data visualization has become a wave of the times. In this context, due to the different types and quantities of data stored in computer systems, different forms of data visualization can be seen in web pages, demonstration slides and papers. However, in many cases, we can’t directly obtain the underlying data, so the classification of chart images becomes very important. Only with the classification technology of chart images can we understand it more intuitively and deal with it more concretely, such as generating new charts according to the extracted data. Using depth learning technology to classify chart images is now a very popular way. In the field of image classification, convolution neural network (CNN) is the most widely used technology in depth learning, not only because of its high accuracy, but also because it encapsulates the process of feature extraction. At the same time, using the software architecture of PCBMER framework to design application programs can maintain high stability of the system. From the experimental results, this new technology is feasible, and the architecture can be further optimized to make the results more accurate.
Research on Colour Modelling and Detecting System Based on Computer Big Data
Authors: Pei Xia , Zhang Li
Published: June 2021

Through the statistics and analysis of the three colour components of dynamic background pixels in RGB space, the paper found that the difference between the three components fluctuates in a narrow area. Based on this fact, it proposes RGB colour based on computer big data Background modelling method of component statistics. This method fully considers the correlation of the three colour components of RGB, and the foreground detection process is faster. Experimental results show that compared with other colour invariant methods, this algorithm can more accurately reduce the computational complexity, time consumption and memory consumption of foreground detection.
Image Enhancement and Improvement Algorithm Based on Esrgan Singal Frame Remote Sensing Image
Authors: Yang Zhiwei , Wang Yunyan
Published: June 2021

Traditional spline interpolation algorithm for reconstruction of visual effects are not good, based on Super Resolution against Network (Super - Resolution Generative Adversarial Network, SRGAN) edge character to deal with such problems as imperfect, using a generated based on the enhanced Super Resolution against Network to improve the Resolution of ordinary optical remote sensing images, the first Network generated by high Resolution data sets to train (G network), then lower Resolution test data model test, The test results and real results are put into the discrimination network (D network) to get the adversarial loss, and then the generated network is modified according to the adversarial loss. The superiority of the network is improved by introducing dense residuals to SRGAN, modifying the judgment object of the discriminator to be relatively real, and using the eigenvalue before activation to improve the perceived loss. The desert, farmland, forest and mountain data were tested on AID data set, and the algorithm in this paper could obtain the recomposition of the real image more closely. Compared with SRResNet and SRGAN algorithms, PSNR improved by about 4.0db and SSIM improved by about 0.14. This method improves the feature comprehensiveness by increasing the network fineness degree, and USES the modified perception loss to get the brightness closer to the real image, which is beneficial to improve the quality of single frame remote sensing image.
Study and simulation of heterodyne optical phase-locked loop for inter-satellite laser interferometer
Authors: Liu Shaokun , Zhong Xingwang
Published: June 2021

Coherent transmission of optical signal is an important module of inter-satellite laser interferometer. Through heterodyne optical phase-locking technology, the coherent transmission of laser signals from the master spacecraft can be achieved. And in the case of ensuring the stability of the local laser frequency, amplifying of the optical output power is realized. This article introduces and analyzes the principle, modeling and simulation of heterodyne optical phase-locking technology, which provides a reference for the realization of laser signal’s coherent transmission from slave satellite.
Face fatigue detection method based on convolution neural network
Authors: Song Yibing , Wang Qiang , Zhai Yantao , Tai Qiang
Published: June 2021

In order to monitor the fatigue state of the face, a state detection algorithm based on a variety of facial fatigue parameters is proposed. Firstly, convolution neural network is used to enhance the edge information of eyes and mouth for accurate positioning. Then, a rotation invariant LBP pyramid feature is used to describe the eyes, and a linear SVM classifier is trained to distinguish the open and closed state of eyes. The open and closed state of mouth is judged according to the open area and aspect ratio of mouth. At the same time, the vertical movement of eyes is counted Determine changes in head position. Finally, based on the state of eyes and mouth and the position of head, four fatigue parameters which can describe the state are calculated, and the final fatigue state is obtained by convolution neural network. The experimental results show that the detection and state discrimination algorithms have high accuracy.
Study of Flame Detection based on Improved YOLOv4
Authors: Cao Chengzhi , Tan Xiaoyu , Huang Xinyi , Zhang Yongjun , Luo Zehao
Published: June 2021

In some complex circumstances, the detection of conflagration mostly depends on smog detectors, which have lots of limitations in precision, efficiency and safety. If we make full use of object detection algorithms to detect the flame in industries, it will benefit people’s safety obviously. Among all kinds of object detection algorithms, YOLO series play a very significant role. In this paper, we propose an improving strategy on YOLOv4 to enhance its precision based on multi-scale feature maps. Firstly, we create flame datasets including almost 4000 high-resolution flame pictures. Secondly, some improvements on feature extraction network are made to detect smaller objects. Finally, the total algorithm are trained and tested on our datasets for about 400 epochs. The result show that the method can generate high quality on flame detection in a great number of situations.
Foreign Object Detection Algorithm Based on Multi-scale Convolutional Network
Authors: Zheng Jiexin , Chen Ye , Zhang Hong , Liu Dan
Published: June 2021

In order to detect foreign matter invading the track and prevent the intrusion of foreign matter from causing railway safety accidents, the detection algorithm of foreign matter intrusion on the track is studied. Aiming at the problem that the rail transit scene is complex and the obstacle scale changes in the acquired image information, this research proposes a multi-scale target detection algorithm based on the YOLO (you only look once) algorithm. First, an adaptive feature fusion module is designed to make the feature maps used for detection have strong semantic information at various scales; then, a new loss function is designed to alleviate the problem of uneven sample distribution and optimize the training process. Experiments show that the algorithm has obvious advantages in multi-scale detection, which not only improves the accuracy of target detection, especially the accuracy of small targets, but also does not significantly increase the inference time and the amount of parameters, and has high real-time performance.
Image Denoising Algorithm Based on Generative Adversarial Network
Authors: Liu Gaoyuan , Zhong Guangyuan , Zhao Huiqi
Published: June 2021

Image denoising is an important research direction of image restoration. With the increasing requirements of image quality, image denoising has been widely concerned by scholars at home and abroad. This paper studies the problem of noise image denoising, using improved sparse representation algorithm and deep learning technology to denoise the noise image. In this paper, a de-noising model based on generative countermeasure network is proposed. The residual algorithm and dense connection are added to the network layer of learning image noise information features. At the same time, the discriminator is trained to judge whether the generated image is true or false, so as to avoid boundary blur while de-noising. Zero filling convolution is used to ensure the consistency of input and output characteristic dimensions of each layer. The output of network model is image noise information. Simulation results show that the algorithm has good denoising performance.
Research on Image Super-resolution Internet Transmission Technology Based on Virtual Optics
Authors: Xiao Gengyi
Published: June 2021

Image resolution is a set of performance parameters used to evaluate the richness of detailed information contained in an image, including temporal resolution, spatial resolution and color scale resolution, etc., which reflects the ability of the imaging system to reflect the detailed information of objects. In this paper, a super-resolution image transmission technology based on virtual optics is proposed. The original image is placed on the object plane of the virtual light path. Firstly, the light wave signal of the original image on the virtual diffraction plane is obtained by inverse diffraction calculation. Then, the light wave of the virtual diffraction plane is illuminated by spherical wave and then the forward diffraction calculation is performed. By changing the position of the observation plane, the original images with different magnification can be reconstructed. The simulation test results show that compared with the general interpolation amplification method, the amplified image has a good visual perception effect, especially in the significant area. The results obtained by the algorithm in this paper are better than the interpolation model and convolutional neural network algorithm as a whole; The above test results objectively show that the super-resolution effect of this algorithm is better.
Research on the Aesthetic Features and Technology of Computer Graphics
Authors: Song Yanbin
Published: June 2021

Computer graphics is a new science produced with the popularization of computers. The processing technology of graphics and images in computer graphics has attracted much attention. How to make reasonable use of them has become an important subject in the field of modern scientific applications. For this research background, this paper proposes an image recognition algorithm based on wavelet and DFB-PCA. After decomposing the recognition image with wavelet transform, DFB-PCA recognition is performed on the low frequency subband. The experimental results show that the method is beneficial to reduce the influence of factors such as illumination, posture and expression, reduce the dimensionality of noise and image recognition, and has better robustness. Compared with directly using PCA recognition on the original image, the calculation speed and recognition efficiency of the image can be improved.
Inspection Robot for Submarine Pipeline Based on Machine Vision
Authors: Yin Fangrui
Published: June 2021

In order to improve the intelligence of submarine pipeline inspection, reduce manpower and material resources, and improve inspection efficiency, an underwater pipeline inspection robot based on machine vision is proposed. This paper introduces the existing pipeline inspection methods and technologies, and analyzes the feasibility of pipeline inspection and inspection technologies based on image processing. On the basis of this subject, the corresponding circuit and embedded system are designed, and the related images are sampled, processed and analyzed, and the images are subjected to threshold segmentation, binarization, edge corrosion and other operations. Furthermore, the experimental site and underwater robot were built, and the pipeline defects were detected in real time by using the recognition method based on neural network.
Research on Detection Algorithm of Roadway Line on Structured Road Based on Vision
Authors: Qian Suke , Yang Jie , He Chao , Li Zonghao
Published: June 2021

To solve the problem of low efficiency of lane recognition in different structured road environments, an improved Hough transform algorithm is proposed. Firstly, every frame of image in the video stream is processed by gray scale and inverse perspective transformation, so as to reduce the amount of data and improve the accuracy of lane recognition. Then, median filtering and wavelet hard threshold denoising are combined to remove noise and improve image quality. Secondly, the image is binarized and edge detected by OTSU algorithm and Sobel operator, and the lane feature information is extracted. Finally, the traditional Hough transform algorithm is improved, and the slopes and points of the selected straight lines in the feature area are averaged, and then a new straight line is obtained and displayed in the image. Simulation experiments show that the algorithm has good applicability and reliability in different structured road environments, and achieves the expected experimental results.
Study on High Precision Fabric Density Measuring Instrument and Measuring Method Based on Moire Fringe
Authors: Wen Xinhui , Sun Haoteng , Wang Meiyan
Published: June 2021

With the continuous development of science and the continuous progress and reform of fabric knitting technology, all kinds of fabrics continue to appear. Linear density is one of the most important physical and geometric characteristics of knitted fabrics, which affects the physical and mechanical properties, feel and style of textiles, and is one of the important bases for fabric design and manufacturing process parameters.In this paper, a device and method is developed, which is not affected by the width and density of fabric lines, and can accurately measure the density of fabric. The invention puts forward a method of measuring fabric density from a new point of view. Using the phenomenon of moire fringes, the fabric density of the fabric to be measured is calculated by measuring the angle. The device has the advantages of simple structure, low production cost, and is not affected by the width and density of cloth lines. it can measure fabrics with high line density or wide lines, and has the advantages of high precision and convenient operation. and the gratings with different grating constants can be selected according to the characteristics of the fabric, which has a very wide range of application.
Application of Fuzzy Recognition in Image Information Recognition
Authors: Huang Junlian , Zhao Dongyan , Lv Boxue
Published: June 2021

Image recognition is to calculate and analyze the information contained in the image, classify it or extract useful information from it. Image recognition technology based on fuzzy recognition is a new type of image recognition technology developed with the development of modern computer technology, image processing, artificial intelligence, pattern recognition theory and so on. It is an image recognition method based on traditional image recognition methods and fusing fuzzy recognition algorithm. This paper verifies the fuzzy recognition program, reads the pixel matrix of the file, and gets a relatively clear image after certain program processing. The simulation results show that the fuzzy recognition method can get more clear and accurate information in the application process of image information technology.
Perceptual losses for self-supervised depth estimation
Authors: Liu Xiaoyu , Gao Huachen , Ma Xiaowen
Published: June 2021

Convolution neural network has shown excellent results in stereo and monocular disparity estimation, while most of the existing methods convert the image depth prediction problem into the image reconstruction problem, and calculate the depth of each pixel through the disparity between the generated left and right images. However, in the reconstruction task, the loss is still calculated at the pixel level when comparing the reconstructed picture with the original picture, which will greatly affect the estimation of picture depth due to the problems of illumination and occlusion. Therefore, when calculating the loss of image reconstruction, it is very important to compare the higher-level features extracted from the reconstructed image with the original image. In this paper, based on the existing methods, we have innovated the loss function and introduced perceptual loss, i.e., we use feedforward neural network to extract features to further evaluate the reconstructed image, to make the reconstruction loss of baseline more accurate and improve the accuracy and robustness of the depth prediction model. To compare the improved effect, we performed extensive experiments on KITTI driving data by the improved model set, and the experimental index obtains better performance than the original baseline model.
Asian Giant Hornets Recognition Using Deep Convolutional Neural Network
Authors: Wang Haochen , Yang Ruofeng , Li Xu
Published: June 2021

We trained 2 deep neural networks to identify whether the images with high resolution in the dataset provided by COMAP contain any Asian giant hornet. We divide the classification problem into two subproblems: feature extraction, and image classification. In order to reduce the impact of sample imbalance, we apply image flipping and Borderline-SMOTE methods for data augmentation first, and then divide the data into the training set and the validation set (testing set). Next, we utilize auto-encoder to collect key features of images and the testing loss dips to 0.0274 after training. Next, we establish the Classification-Net to solve the identification problem based on the features just extracted, and the accuracy in testing set reaches 0.8030. Finally, we summarize the main features of having negative labels from three aspects: species characteristics, subject definition and background softness.
Pavement Crack Detection Method of Street View Images Based on Deep Learning
Authors: Shu Zekai , Yan Zhaoyu , Xu Xihang
Published: June 2021

Pavement crack detection is a challenging task for carrying out pavement maintenance works. Deep learning method is regarded as an effective and accurate way to detect pavement cracks. However, this often requires a large dataset composed of different crack images. This paper introduces a convenient and low-cost method to collect pavement images by using street view images. 400 images from 5 cities are collected and labeled to form the dataset. Then, it is applied to train a target detection network YOLOv5, which is the latest version of YOLO network. The result shows that this network can effectively detect crack with mAP of over 70% and detection time of 152ms, which are all better than another classical method YOLOv3. Considering the easiness of collecting images, this method can be a suitable way to evaluate the pavements.
Research on Machine Vision Effect Based on Graph Neural Network Decision
Authors: Huo Jide , Sun Weining , Dai Huaixuan
Published: June 2021

With the continuous expansion of the scale of the network, modeling the complex graph structure is a major challenge for the recommendation task. There are conflicts between these complex information, which will directly affect the recommendation results. For this reason, a graph neural network recommendation method based on multi-branch decision is proposed. The algorithm models the social network graph and the user project graph through the neural network, connects the two graphs intrinsically, and learns the feature vectors of the target users in the social space and the project space. Then two feature vectors are connected in series by MLP to extract the potential feature vector of the user. Finally, the prediction score is generated by integrating the probability matrix decomposition model. In this method, the graph neural network is used to model the program data and dependence graph, and the effective program features are automatically extracted from the source code, and then the extracted features are input into the downstream model for loop vectorization parameter prediction. Finally, the attention mechanism is used for information fusion to get the final session representation and predict the next interactive item. Comparative experiments are carried out under the two scenarios of e-commerce and civil aviation respectively. The experimental results show that, compared with the optimal benchmark model, the improvement of MGSP model on each index of e-commerce data set is more than 1%, and that of civil aviation data set is about 3%, which verifies the effectiveness of MGSP model. On the LLVM cyclic vector test set, the proposed method achieves a speedup of 2.08 times and improves the performance by 12% compared with the existing methods. In order to solve the problem that the existing deep learning model considers the program code as a serial sequence and misses a large performance optimization space, a new program heuristic method based on depth map network is proposed to achieve optimization.
Research and Application of LDA Model in Movies Images Based on the Visual Effects of Computer Images
Authors: Zheng Yitian
Published: June 2021

With the advent of the image age, the popularity of war-themed film and television dramas in the new century has promoted a new wave of thematic narratives. Facing the era of computer graphics, the main theme narrative adopts a series of new reconstruction strategies, namely: the spectacle strategy of visual expression, the typification strategy of narrative subjects, and the striation strategy of character modelling. As an important genre of Chinese movies, war-themed themed movies often focus on the education and dissemination of national ideology, but “The Eight Hundred” broke the stereotype of this type of movie to the audience. Taking the film “The Eight Hundred” as an example, using the LDA model of computer image characteristics, combined with the related theories of visual effects, the thesis explores how the main theme of contemporary warfare movie content is expressed through images and its unique image style.
Research on the Application of Visual Maps Based on CiteSpace in Speech Technology
Authors: Yin Jiake
Published: June 2021

In recent years, deep learning has been widely used in the field of speech technology, and provides people with an efficient and convenient way of obtaining information and communicating in most application scenarios. This paper uses CiteSpace information visualization software to visually analyze the speech technology research literature based on nearly 10,000 papers in the field of speech technology research and application from 2013 to 2021. From the perspective of bibliometrics, this paper analyzes the distribution of hotspots and research frontiers in speech technology research in countries, institutions, disciplines and other information visualization maps, and compares and analyzes the literature information in the field of speech technology research and application at home and abroad in recent years. The research results show that the main disadvantages of speech technology at home and abroad are: the inability to completely avoid noise interference; the inability to correctly identify ambiguous and generalized sentences; and the inability to idealize the radio remotely. Aiming at the problem of noise interference, this paper proposes a deep learning-based noise reduction algorithm and increases the number of convolutions of the neural network to improve the model; then, for the ambiguity and generalization in the recognition process, this paper proposes a deep learning-based unsupervised training method; Finally, for the problems of sound reception and echo, this paper proposes a far-field sound pickup technology based on multi-channel signal microphone collection.
A Method of Brain Image Optimization based on an Autoencoder Unet
Authors: Chang Haipeng
Published: June 2021

As data and computer science grows rapidly in the modern era, numerous branches of technology appears one ofter another, medical imaging is one of them. After medical scans were first conducted as part of medical detection, prognosis, and treatment, methods such as CT, PET, and MRI scans. The precision of medical images is highly demanded for determination of lesion inside the human body. However, due the the variety of noise possibly taking place in the scan, and of how to prevent them each, it is merely impossible to avoid all images from being affected. A solution to this is denoising. Though many denoising methods had been leveled in the past decades, most traditional ones hold the possibilities of losing border information. In response to this specific issue, this paper will focus on using deep learning computation to generate a methods that is highly efficient and keeps images intact at the same time. This involves using unsupervised learning, convolutional neural network, U-net, and autoencode to create a process of the computer learning by itself to improve medical image qualities. With this accomplished, medical image quality can be thrown out of concern for doctors, lifting enormous weight of off their shoulder with the ever-growing population of patients.
Analysis of Wasp Transmission through Prediction Classification Model and Support Vector Machine
Authors: Wei Bao , Liu FangChao , Dong YuTing
Published: June 2021

Due to the hazards caused by Vespa Mandarinia, the public reports collected in Washing-ton State were classified. Therefore, two models were established in this paper: The Grey Pre-diction Model and the Prediction Classification Model. We begin with the Grey Prediction Model to predict the problem of whether a pest can spread over a period of time. Based on the gray scale prediction theory and combining with experts’ identification of the sighting report as the data of Vespa Mandarinia, GM (1,1) model has been established by using the gray scale prediction method.