bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Statistics in Volatile Analysis by Accurate HS-SPME-GC/MS Measurement and Calculation
Authors: Zhang Ming , Du Liqing , Shuai Xixiang , Ma Feiyue , Li Ya , Qiao Jian , Tu Xinghao
Published: December 2021

The volatile flavor compound in oil is an important indicator of quality which is widely used in the industry to assess the commercial value of oil. The volatile compounds of moringa seed oil were investigated by HS-SPME-GC/MS. The results showed that 52 volatile compounds were identified in moringa seed oil, including 12 hydrocarbons (20.66%),3 acids (23.99%),8 alcohols (8.28%),2 esters (2.61%),8 aldehydes (14.58%),2 ketones (0.82%),7 phenols (6.25%) and 10 heterocyclics (8.74%). Due to the low sensory threshold and high relatively content of aldehydes, aldehydes is one of the mainly factors to affect the flavor of moringa seed oil.
Application of computational fluid dynamics in the research on odorous-black water and physical treatment technology
Authors: Guo Chao , Wei Yulu , Liu Siqi
Published: December 2021

As an extreme phenomenon of water pollution, odorous-black water not only cause ecological damage and threaten human health, but also severely restrict urban development. This paper mainly summarizes the main points, applicability, advantages and disadvantages of the current comprehensive treatment technology of odorous-black water, and analyzes the later development direction of odorous-black water treatment technology. It is considered that the treatment of odorous-black water is a systematic project, which involves many sources such as external source interception, water purification, quality assurance of living water, ecological restoration are the important technical means.
Research on object detection algorithm based on deep learning for mobile Terminal
Authors: Luo Jie , Ye Jufeng , Shan Lan , He Qunying
Published: December 2021

In order to improve object detection ability of robot, this study introduces an object detection algorithm which is based on deep learning. Firstly, a neural network that contains Convolution Layer, Pooling Layer and Fullly Connection Layer is designed to recognize whether the target object in image. Secondly, the Faster-RCNN, as a typical object detection algorithm, is used to detect the position of target object in image. Finally, the algorithm is transplanted on Raspberry Pi for deployment and testing. Results show that this algorithm can work well on Raspberry PI, and the mAP (mean average precision) and FPS (frames per second) reach 97% and 3. Meanwhile, the position of target object is accurately marked in image. Therefore, this study implies that the object detection algorithm based on deep learning can be implemented on mobile terminal and is helpful to improve object detection ability of mobile terminal.
Application of differential countermeasure machine learning model in the field of UAV circuit inspection
Authors: Huang Xinrui
Published: December 2021

In this paper, we establish one-objective differential game equations for one-to-one attack and defense in a two-dimensional plane. Through calculation and visual analysis, obtain the optimal pursuit path movement trajectory, and through machine learning method to training UAV, using cycle process of simulation, output with time growth each cycle pursuit path results, by comparing the movement trajectory image of the pursuit results and find the sheep just escape critical point exit. After that, the angle difference between the two initial positions was changed and tested again to enable the UAV to learn the optimal escape strategy more comprehensively, thus making a more precise path selection. Finally, this method can be reasonably evaluated.
Application of Intelligent Sensors in Biomarker Detection Using Accurate Data Measurement and Calculation
Authors: Chen Hao
Published: December 2021

Cancer has been one of the most serious health issues of the 21st century. Although improvements in the treatment of cancer with new pharmaceutical products and technology remain a significant challenge for cancer biologists and oncologists. Early and accurate screening and analysis technology to diagnose the disease are essential for improving the survival rate and reducing mortality and morbidity. Scientists have discovered the clinical application of cancer biomarkers for cancer diagnosis and treatment. Biosensors technology appears to be the only hope for timely diagnosis and treatment of cancer, since they exhibit remarkable analytical performance. In this review, we will discuss about basic knowledge and classification of biosensors, common cancer biomarkers and some applications of biosensors in cancer biomarker detection.
Accurate detection method of moving target based on sequential SAR images with multiple azimuth squint angles
Authors: Yang Shiqi , Liu Yang , Xi Peili , Li Chunsheng , Yang Wei , Zeng Hongcheng
Published: December 2021

In this paper, a novel moving target detection method for sequential Synthetic Aperture Radar (SAR) images with different azimuth-squint angles is proposed. In sequential SAR images, due to the movement of the target, the imaging position of moving targets among different frames differs. The method proposed in this paper uses this kind of motion characteristics to achieve the detection of moving targets in multi-frame SAR images. This algorithm can be divided into two parts: block-level detection and pixel-level detection. Block-level detection is achieved by stacked denoising autoencoders to extract the high-dimensional features of the moving target. Pixel-level detection consists of Local Binary Similarity Patterns (LBSP) coding as well as grayscale background subtraction. Pixel-level detection only needs to consider the pixels of foreground image pieces which contain moving targets. This method can not only increase the detection speed, but also suppress the false alarm problem caused by clutter. Experiments are carried out for verifying the validation of the method and the comparison are made between the proposed method and the traditional Constant False Alarm Rate (CFAR) algorithm.
Analysis of Ionospheric Disturbance on X-band SAR Image Registration
Authors: Liu Huixiang , Liu Yang , Xi Peili , Chen Jie , Yang Wei , Zeng Hongcheng
Published: December 2021

The atmosphere is a very important factor that affects the accuracy of X-band SAR image registration, and the ionosphere effect has the most intricate influence. In response to this problem, this paper introduces the mathematical model of ionospheric dispersion effect and scintillation effect. Then, echo simulation, imaging processing, and image registration are used to calculate the image offset caused by the ionosphere, which can determine whether the ionosphere effect needs to be compensated during image registration. Simulation experimental results show that in the X-band image registration, the dispersion effect needs to be compensated, and the impact of the scintillation effect can be ignored.
Research on Topology and Control System of High Power Grid Simulator
Authors: Li Houxiang , Zhang Yongming , Zhai Hongyu
Published: December 2021

Grid simulator can simulate the output of various types of power grid failure to test wind power grid-side equipment, in the design of high-power grid simulator, due to the switching frequency restrictions, will affect the control bandwidth, resulting in the power grid simulator system performance decline. Therefore, the modular multi-level converter (MMC) with higher equivalent switching frequency is used on the inverter side of the grid simulator, and the bridge arm circulation suppression strategy based on the second-order generalized integrator (SOGI) and vector scale integral (VPI) resonant controller is proposed for the internal bridge arm circulation of the converter. Finally, based on RT-LAB, the network simulator controller hardware in the ring (CHIL) experimental platform is built and experimented, the experimental results show that the design of high-power power grid simulator system can simulate the output to obtain the required grid failure.
Energy Storage Technology Used in Smart Grid
Authors: Fu Qiang , Fu Chengxi , Fu Peng , Deng Yuke
Published: December 2021

Energy storage is one of the main problems bothering the power system. The present research situation of energy storage is outlined. The working principles, development process and technical features of pumped storage, compressed air energy storage, flywheel energy storage, electromagnetic energy storage and chemical energy storage are described in detail. The application prospect of energy storage is proposed.
Effect of Computational Parameters on Output Properties of Underwater Explosion by Intelligent Numerical Simulation
Authors: Zheng Yonghui , Wei Jifeng , Xiao Rui
Published: December 2021

The computational parameters are of great influence on underwater explosion load. A one-dimensional wedge model is established to analyze the influence of boundary condition (BC), water domain and mesh density on the numerical simulation results. The results show that flowout BC is rigid boundary and transmit BC is not suitable for simulating the collapses phase of bubble pulsation. According to propagation distance of shock wave and its reflected wave, a simple method to calculate appropriate water domain is proposed. A positive correlation between mesh density (λ) and calculated peak pressure of shock wave (P
m) is found. When λ tends to infinity, simulated Pm in near field is quite reliable, but the values in relatively far field are lower than empirical results.
Application of Recommendation Algorithm and Big Data Technology in Computer English Corpus Database
Authors: Wang Qingling
Published: December 2021

Corpus linguistics is one of the branches of modern linguistics. It is also a cutting-edge research problem of modern linguistics spawned by the background of the information technology era. Corpus linguistics can reset the teaching role of English majors. College English vocabulary teaching makes use of the corpus’s abundant real language materials and the computer’s ability to analyze and process large-scale corpus, guide students to explore the usage of vocabulary in the context, and use the corpus to deepen students’ autonomous learning. This article will start with the development of corpus linguistics, explain the necessity of combining corpus and English language teaching, and propose a corpus linguistics-based English language learning platform system in colleges and universities, and combine with semantic recommendation algorithms to verify that the system is in English learning.
The Computer Intelligent Selection of Scientific Research Subjects Through Ensemble Learning for Large-Scale Data Sources and Deep Neural Network
Authors: Ma Yan , Zou Lida , Liu Ke , Han Yingkun , Ma Lei
Published: December 2021

Selecting a proper scientific research subject is critical for scientific researchers and managers. Scientific researching data are from massive sources and have various attributes. For the problem of subject selection, feature extraction and prediction model play important role in performance optimization. In the paper we introduce ensemble learning method to help find the best fit attributes describing data. Our ensemble learning models include random forests, support vector machine, Boltzmann machine and decision tree. Since the data are from many data sources, we adopt multiple models of deep neural network. An acceleration method is used to reduce the training time as well. Experiments shows that the proposed approach performs better than RNN algorithm both in accuracy ratio and recall ratio. The model selection module and acceleration method help optimize the time cost largely.
Research on Dynamic Knowledge Map Service System Using Computer Big Data
Authors: Zhang Nan , Zhang Wenqiang , Shang Yingnan
Published: December 2021

The emergence of computer big data related data provides a new method for the construction of knowledge links in the knowledge map. This realizes an objective knowledge network with practical significance that is easier to be understood by machines. The article combines the four principles of linked data publishing content objects and their semantic characteristics, and uses the RDF data model to convert unstructured data on the Internet and structured data that adopts different standards into unified standard structured data for association. The system forms a huge knowledge map with semantics, intelligence, and dynamics.
Mathematical Multivariate Statistical Analysis and Big Data Information System Establishment on Urban Pollutant through Intelligent Computational Method
Authors: Guo Mingyue
Published: December 2021

This paper mainly adopts the actor analysis and correspondence analysis in multivariate statistical analysis., for 6 indicators of the main pollutant contents emission in waste gas by 31 cities in China. The results of Factor Analysis showed that with cities in 6 indicators were controlled by two independent factors. The 2 factors, which were determined and named, were f
1, domestic waste gas pollutant emission factor, and f
2, factor of Industrial waste gas pollutant emission. The percentage of accumulated contribution of variances was 85.51%. The result s of correspondence analysis showed that, six indicators and cities which had significant or close relationships with 31 cities.
Dynamic Response Measurement of Elastic Structures Through Smart Digital Image Correlation Method and Calculation
Authors: Wang Jiawen , Liang Jingqi , Wang Rui , Qi Xiaobin
Published: December 2021

Based on the proper improvement and development of the basic principle of digital image correlation method, a 3D-DIC measurement system is built. Its measurement principle and application process can be divided into four steps: camera calibration, image acquisition, image matching and three-dimensional reconstruction. The measurement system can realize non-contact and full-field measurement and has the advantages of not being affected by the test environment, not imposing additional mass on the test model, and high signal-to-noise ratio of the measured data. Taking the elastic plate model as an example, the accuracy and reliability of the measurement system in the measurement of static and dynamic displacement response are verified by using the measurement results of laser displacement meter as a reference. In addition, the tensile strain of the projectile aluminum alloy tail model and the ground mode of the elastic plate are tested to further verify the practicability of the test system.
Computer Assisted Chord Detection Using Deep Learning and YOLOV4 Neural Network Model
Authors: Ru Yingdong
Published: December 2021

Music symbol recognition is an important part of Optical Music Recognition (OMR), Chord recognition is one of the most important research contents in the field of music information retrieval. It plays an important role in information processing, music structure analysis, and recommendation systems. Aiming at the problem of low chord recognition accuracy in the OMR recognition model, the article proposes a chord recognition method based on the YOLOV4 neural network model. First, the YOLOV4 network model is used to train single-voice scores to obtain the best training model. Then, the scores containing chords are trained through neural network fine-tuning technology. The experimental results show that the method recognizes the chords with great results, the model was tested on the test set generated by MuseScore. The experimental results show that the accuracy of note recognition is high, which can reach the accuracy of duration value of 0.96 which is higher than the accuracy of note recognition of other score recognition models.
Research on the peak prediction and intelligent computing of reversal error for the tilt feed system installed on the precision machine tools
Authors: Feng Bin , Yang ManZhi , Dang Meng
Published: December 2021

To effectively predict the peak of reversal error of tilt feed system and reduce reversal error caused by friction and gravity components, a peak prediction method of reversal error for tilt feed system on the precision NC machine tool is proposed. According to the load, tilt angle, motion trajectory, maximum static friction torque and relevant dynamic characteristic information, the peak prediction formula of the reversal error for the tilt feed system is established by mathematical derivation based on the kinematics, dynamics and torque balance during the process of reversal. Thus, the peak of reversal error for the tilt feed system can be obtained. The experimental results show that this method can achieve a good prediction effect, and can predict the peak of reversal error before the machining. It provides a theoretical basis for the reversal error suppression.
Study on a visual coder acceleration algorithm for image classification applying dynamic scaling training techniques
Authors: Huo Junliang , Ling Jiankun
Published: December 2021

Nowadays, image classification techniques are used in the field of autonomous vehicles, and Convolutional Neural Network (CNN) is used extensively, and Vision Transformer (ViT) networks are used instead of deep convolutional networks in order to compress the network size and improve the model accuracy. The ViT network is used to replace the deep convolutional network. Since training ViT requires a large dataset to have sufficient accuracy, a variant of ViT, Data-Efficient Image Transformers (DEIT), is used in this paper. In addition, in order to greatly reduce the computing memory and shorten the computing time in practical use, the network is flexibly scaled in size and training speed by both adaptive width and adaptive depth. In this paper, we introduce DEIT, width adaptive techniques and depth adaptive techniques and combine them to be applied to image classification examples. Experiments are conducted on the Cifar100 dataset, and the experiments demonstrate the superiority of the algorithm on image classification scenarios.
Grasp Detection Based on Light-Weight Hierarchical Fusion Convolutional Neural Network
Authors: Xu Ziang
Published: December 2021

This paper presents a light-weight Hierarchical Fusion Convolutional Neural Network (HF-CNN) which can be used for grasping detection. The network mainly employs residual structures, atrous spatial pyramid pooling (ASPP) and coding-decoding based feature fusion. Compared with the usual grasping detection, the network in this paper greatly improves the robustness and generalizability on detecting tasks by extensively extracting feature information of the images. In our test with the Cornell University dataset, we achieve 85% accuracy when detecting the unknown objects.
Application of Machine Vision Recognition System in Mobile Robot
Authors: Fu Yan
Published: December 2021

In order to solve the problem of autonomous recognition of hexapod robot and realize the intelligent and humanized development of robot, OpenMV is taken as the main platform, hexapod robot is taken as the main machine carrier, Python is taken as the main development language, C language is taken as the auxiliary development language, and the reasonable application of image processing technology is added. A simple visual recognition system based on OpenMV is designed to realize the application of visual recognition.
Intelligent Calculation Method and Algorithm Optimization of Consumption Reducing for SCR and SNCR in Denitriation System
Authors: Li Kaiqiang , Chen Xiaobing
Published: December 2021

Since the environmental laws have been more and more strict about pollutants emissions of thermal power plant, SNCR and SCR system seems to be typical configuration. However the ammonia consumption calculation differs from different designers. In this paper the popular and experienced calculation method is introduced for thermal power plant dinitriation system.
Research on Character Computer Intelligent Recognition of Automobile Front Bar Bracket Based on Machine Vision
Authors: Shen Chuanxing , Zhu Yongjian , Wang Chi
Published: December 2021

Aiming at the problem that the characters in the superimposed character area on the surface of the front bumper bracket of the car are difficult to recognize, a machine vision-based automobile front bumper bracket character recognition method is proposed, use Python, OpenCV and Halcon computer vision library for software system design. For eight images collected from different angles of light source directions, an innovative method of polynomial fitting gray value can reducethe uneven illumination of the images. The photometric stereo algorithm is used to obtain a high-contrast character image, and the separation of the two types of characters is simultaneously achieved. After the image filtering, opening and closing processes canremove background interference, use a morphological improvement algorithm based on scanning algorithm to complete character positioning, and then the improved algorithm of projection dichotomy based on the connected domain size is used to complete the character segmentation, and finally the support vector machine is used for character feature recognition. The experimental results claim that these methods can quickly separate superimposed characters and complete the recognition of non-color difference convex characters and inkjet characters, and the average recognition accuracy rate is over 96%, which meets the expected recognition requirements.
A Novel Back Propagation Neural Network Optimized by Rough Set and Particle Swarm Algorithm for Remanufacturing Service Provider Classification and Selection
Authors: Cao Jianhua , Xia Xuhui , Wang Lei , Liu Xiang , Zhang Zelin
Published: December 2021

Aiming at the problem that the high classification feature dimensionality of the back propagation neural network (BPNN) leads to slow convergence speed and the initial weight and threshold sensitivity of the BPNN lead to the problem of easy convergence to the local optimum. A novel BPNN optimized by rough set and particle swarm algorithm (RS-PSO-BPNN) for remanufacturing service provider classification and selection is proposed. First, the attribute reduction method of rough set theory is used to preprocess the classification features of remanufacturing service providers, redundant attributes are deleted from the decision table, and the input feature dimension is reduced; then the PSO algorithm is used to optimize the network Initial weight and threshold. Finally, the proposed method is used for the selection and optimization of remanufacturing service providers. The results show that the proposed RS-PSO-BPNN has higher classification accuracy and efficiency for the problem, which provides scientific decision supports for remanufacturing service provider selection.
Research on Airborne Electromagnetic Whole-area Apparent Resistivity Imaging Algorithm in the Detection of Goaf in Rail Transit
Authors: Jia Yajuan , Zheng Jianbo , Zhou Hongfang
Published: December 2021

Depth apparent resistivity imaging is an important process of data processing and analysis in the aviation transient electromagnetic method. It can provide reference value of conductor depth, vertical extension, and other information, and can accurately provide the measurement of each aviation transient electromagnetic measurement system. The structural section of the apparent conductivity of the one-dimensional layered medium on the line. As an advanced geophysical exploration technology, the aerial transient electromagnetic method has been applied significantly in the exploration of polymetallic minerals abroad in recent years. In this paper, based on the theory of ground-to-air transient electromagnetic method with multiple radiation sources, a corresponding multi-component global apparent resistivity definition method is established. The advantages of using the magnetic field strength to define the global apparent resistivity of the multi-radiation field source ground-air system are analysed. For each component of the magnetic field strength, respective global apparent resistivity algorithms are proposed to realize the multi-component, full-time, and full-space visual resistivity. The resistivity is calculated, and the influence of the offset on the global apparent resistivity is analysed. By adjusting the relative position of the source and the current direction and other parameters, the multi-radiation source transient electromagnetic ground-air system can not only strengthen the signal strength of different components, weaken random interference, but also better distinguish the location of underground anomalies
Research on Aiming and Tracking Ability Evaluation Model of Laser-guided Missile
Authors: Li Wuzhou , Lin Shicong , Liu Zehui
Published: December 2021

Laser guidance is a continuous process, during which a lot of operational data and corresponding changes are generated. Aiming at the live-fire drill shooting training and assessment evaluation of a certain type of laser-guided missile, this paper analyzes the principle of laser guidance, studies the weighting system of the information field based on the importance of characteristic intervals, integrates and processes the data and outputs the aiming effect picture and sheet, and constructs the aiming and tracking ability evaluation model. Stationary targets and moving targets are tested respectively, and the verification model can realize the calculation of laser information field, the integration of coordinate data, the output of aiming effect diagram, and the evaluation of the shooter’s aiming and tracking ability expressed in a percentage system. The model realizes data collection, integration and processing based on MATLAB software, and builds graph and table output ports, which can realize low delay processing of a large amount of short-term data.
Design of computer network security storage system based on cloud computing technology
Authors: Wang Xi , Shi Lei
Published: December 2021

Nowadays, computer networks are widely used. Besides the convenience, people also feel the pressure of network viruses and hackers. At present, in the process of fighting against network security threats, traditional defense measures have been difficult to meet. Therefore, in order to meet the needs of computer network security under cloud computing technology, and for the future of cloud computing high-quality network storage system can be gradually optimized. In this paper, from the cloud computing and network security storage system two aspects of the computer network security storage performance analysis and design; Then from the design framework, through careful design, to ensure the reliability and security of data upload, storage.
Research and Application of Cloud Computing and Big Data Technology
Authors: Hui Bingran
Published: December 2021

The combined application of new network technologies with the traditional Internet and industry has enabled new businesses such as the Internet of Things and cloud computing to be gradually derived. To realize the construction of a modern society in China, great attention should be paid to the application of new network technologies such as cloud computing in actual work. Now through data integration and correlation analysis, the accuracy and innovation of information are further realized, and the overall work efficiency and work quality are improved. This paper systematically analyzes the network big data technology and applications of cloud computing and Internet of Things, and conducts research from data collection, data integration, data processing, and data governance. Its main purpose is to make the value and function of these new network technologies fully utilized
Matching calculation of accidental movement protection device for elevator Car
Authors: Zhao Zhihui
Published: December 2021

The cage accidental movement protection system is an important protection system of elevator. The basic principle and structure of the cage accidental movement protection device are described. Combined with the whole process from accidental movement of the cage to the operation of the protection device, the theoretical calculation and judgment principle of the accidental movement of the cage protection device are introduced. Aiming at the requirement of the matching calculation of the accidental movement protection of elevator car, the selection of several key parameters which affect the matching calculation of the accidental movement protection of elevator car was proposed. The influence of several key parameters on the matching calculation is analyzed, and the parameter selection is discussed based on relevant standards, and feasible solutions are proposed. These schemes provide a reference for the selection and matching calculation of accidental movement protection devices.
Simulation of Combustion and Alkali Metal Distribution in Zhundong High Alkali Coal Boiler Based on Computer Control System
Authors: Gao Guodong
Published: December 2021

Restricted by Xinjiang’s special geographical location, economic conditions, transportation and other factors, Zhundong coal can’t be sent out on a large scale, which seriously hinders the development of Zhundong coal base. Meanwhile, due to the coal-forming history and Xinjiang’s special natural geographical environment, the alkali metal content in Zhundong coal is generally over 2%, which is much higher than that of power coal in other parts of China. In this paper, based on computer control system, the combustion and alkali metal distribution in Zhundong high alkali coal boiler are simulated, and the morphological distribution characteristics and migration laws of alkali metals such as Na and K in pulverized coal combustion process of high alkali coal, low alkali coal and their two coal samples are deeply studied. Combustion characteristics and heat flow distribution, the simulation results show that the flue gas temperature at the furnace outlet is 895.07°C, and the flue gas temperature near the wall is low, which is helpful to alleviate the slagging and contamination in the furnace.
Possibilities of R programming language in simulating microbiological synthesis processes
Authors: Nikitina Marina A. , Chernukha Irina M.
Published: December 2021

Information technologies of biotechnological processes are based on the use of mathematical models to describe microbiological synthesis. Application of digital technologies in analysis of microbial growth patterns is mainly determined by the ability of modern programming languages to numerically integrate systems of differential equations describing the development of the microbial process in time. In Jupyter Notebook environment in the R programming language, the solution of the kinetic growth model of the E.coli microbial population was shown. Two solution methods were used - the one-step Runge-Kutta method of the fourth order of accuracy and the universal solver ODE (General Solver for Ordinary Differential Equations). Initial data of the problem in question:

K
s

S
0

=
2

(Ks
is substrate affinity S
0 constant for the biomass (microorganism), S0 is initial concentration of substrate); replicating cells m

a0 = 0.01; total number of cells m
0 = 0.05; stoichiometric ratio Ys
= 0.5; various ratios 1)

1
)

λ

μ
m

=
0.0357
;

2
)

λ

μ
m

=
0.0714
;

3
)

λ

μ
m

=
0.1071
;

4
)

λ

μ
m

=
0.1428
;
5
)

λ

μ
m

=
0.2142

(λ is specific growth rate of dividing cells, μm
is inactivation rate constant). As a result, the simulation and verification of microbial biomass growth process - its visual representation in the form of tabular and graphical data were carried out. In the process of simulation of E.coli growth the following peculiarity was revealed. In addition to cell division, a fairly intensive loss of their ability to divide occurs. This process is supposedly determinant in population development and limits the growth and ultimate density of the culture. Thus, information technology will help the researcher not only in studying the process, establishing patterns and predicting results, but also in making reasoned decisions.
Development of a system SIEMNED for integrated modeling of processes in tokamak installations
Authors: Zhilkin A S , Sychugov D Yu , Vysotsky L I , Sadykov A D , Soloviev S Yu
Published: December 2021

The paper describes a new system of integrated modelling SIEMNED (Software and Information Environment for Modelling and Numerical support of Experiments on complex Devices) designed for numerical support of experiments on tokamak installations. Also discussed are the results of its application to the modelling of discharge scenarios at the T-15 MD installation, which is currently being prepared for the physical launch.
Mathematical modelling of optical radiation transport in biological tissues under the conditions of moveable integrating spheres registration
Authors: Karpova T K , Kovalenko N V , Aloian G A , Ryabushkin O A
Published: December 2021

To describe the propagation of radiation in biological tissue, it is crucial to know the tissue’s optical characteristics. Integrating spheres method is widely used for experimental determination of optical properties of biological tissues. In this method, radiation scattered by the test sample in forward and backward directions is detected by the integrating spheres, along with the radiation that passed through the sample without scattering. In order to increase information content of the measurements, a moveable integrating spheres method was proposed, allowing one to register scattered radiation at different distances from sample surface to sphere ports. In this work, using the multilayer Monte Carlo method a numerical simulation of radiation propagation in a turbid medium was carried out under the conditions of detecting scattered radiation by moveable and stationary integrating spheres. Random errors were added to the direct problem solution in order to simulate experimental inaccuracies. The corresponding inverse problems were solved and the errors arising in the determination of optical properties (albedo, scattering anisotropy, optical depth) were compared in the cases of moveable and fixed spheres. It is shown that the same error in the inverse problem input data leads to smaller root-mean-square deviation from the true values when reconstructing albedo and anisotropy with the moveable spheres method, compared to the classical stationary spheres approach.
Mathematical Modeling of Soliton-Like Modes at Optical Rectification
Authors: Kalinovich Aleksey A. , Zakharova Irina G. , Komissarova Maria V. , Sazonov Sergey V.
Published: December 2021

We discuss the results of numerical modeling of forming optical-terahertz bullets at the process of optical rectification. Our calculations are based on a generalization of the well-known Yajima - Oikawa system, which describes the nonlinear interaction of short (optical) and long (terahertz) waves. The generalization relates to situations when the optical component is close to a few-cycle pulse. We study the influence of the number of optical pulse oscillations on the formation of an optical-terahertz bullet. We develop original nonlinear conservative pseudo-spectral difference scheme approximating the generalization of the Yajima-Oikawa system. It is realized with the help of FFT algorithm. Mathematical modeling demonstrates scheme efficiency.
Noether symmetry approach in f (T, B) teleparallel gravity with a fermionic field
Authors: Myrzakulov Yerlan , Bekov Sabit , Myrzakulov Kairat
Published: December 2021

In this work, we consider a homogeneous and isotropic cosmological model of the universe in f (T, B) gravity with non-minimally coupled fermionic field. In order to find the form of the coupling function F(Ψ), the potential function V (Ψ) of the fermionic field and the function f (T, B), we found through the Noether symmetry approach. The results obtain are coincide with the observational data that describe the late-time accelerated expansion of the universe.
Travelling wave solutions for the generalized Schrödinger equation
Authors: Shaikhova G.N. , Rakhimzhanov B.K. , Zhanbosinova Zh.K.
Published: December 2021

In this work, the generalized nonlinear Schrödinger equation is investigated. This equation is integrable and admits Lax pair. To obtain travelling wave solutions the extended tanh method is applied. This method is effective to obtain the exact solutions for different types of nonlinear partial differential equations. Graphs of obtained solutions are presented. The derived solutions are found to be important for the explanation of some practical physical problems.
Deconvolution of induced spatial discretization filters subgrid modeling in LES: application to two-dimensional turbulence
Authors: Boguslawski A , Wawrzak K , Paluszewska A , Geurts B J
Published: December 2021

The paper presents a new approximate deconvolution subgrid model for Large Eddy Simulation in which corrections to implicit filtering due to spatial discretization are integrated explicitly. The top-hat filter implied by second-order central finite differencing is a key example, which is discretised using the discrete Fourier transform involving all the mesh points in the computational domain. This discrete filter kernel is inverted by inverse Wiener filtering. The inverse filter obtained in this way is used to deconvolve the resolved scales of the implicitly filtered velocity field on the computational grid. Subgrid stresses are subsequently calculated directly from the deconvolved velocity field. The model was applied to study decaying two-dimensional turbulence. Results were compared with predictions based on the Smagorinsky model and the dynamic Germano model. A posteriori testing in which Large Eddy Simulation is compared with filtered Direct Numerical Simulation obtained with a Fourier spectral method is included. The new model presented strictly speaking applies to periodic problems. The idea of recovering a high-order inversion of the numerically induced filter kernel can be extended to more general non-periodic problems, also in three spatial dimensions.
Mean-field parameters of some PrxTb(1-x)Al2 compounds found via searching for the best magnetic heat capacity fitting
Authors: Tedesco J. C. G. , Monteiro V.J. , Carvalho A. M. G. , Cardoso L.P. , Coelho A. A.
Published: December 2021

Simulations of the magnetic heat capacity of some (Pr, Tb)Al2 compounds were performed using the mean-field approach. The developed routine aims to optimize the set of mean-field parameters. The proposed algorithm calculates the sum of squared differences between the experimental points and the simulated curve and then changes the parameters in order to minimize this sum. This searching leads to consistent values that can reproduce the experimental data. The parameters found in this work reproduced the heat capacities curves of the PrxTb(1−x)Al2 compounds, x=0.25, x=0.50 and x=0.75, with good agreement. The physical limitations of the mean-field approach do not preclude analysing the results. These parameters are important because they can help to understand and calculate the magnetocaloric effect these materials can present.
Rutherford’s extended formula and optimization of the gravity assists beam modelling in the Solar system
Authors: Grushevskii A , Golubev Yu , Koryanov V , Tuchin A , Tuchin D
Published: December 2021

Rutherford’s formula for the scattering of charged α-particles in the Coulomb field can be easily generalized to the case of gravitational scattering. The extended Rutherford formula for the gravitational scattering is presented. One of the types of the gravitational scattering in the Solar system is the gravity assist maneuvers. In this paper, an effective gravitational scattering cross-section is introduced by analogy for them and the generalized Rutherford formula for gravitational scattering is presented out when performing gravity assists. Modern methods of the ballistic design of the interplanetary space flights using gravity assist maneuvers around planets [1-3] are associated with the need to calculate a lot of trajectories (i.e. of the phase beams). For their effective use it is necessary to study the structure of non-linear flyby gravitational scattering using the Rutherford’ formula and to construct the corresponding effective modelling using according regularized phase beams. It is shown that with using of such approach, it is possible to significantly increase the efficiency of the recurrent procedure for the gravity assists chains searching for ballistic scenarios of the modern interplanetary flights.
Energy-Variation Analysis and Orbit-Complexity Quantification
Authors: Kasolis Fotios , Clemens Markus
Published: December 2021

In state-recurrence analysis, recurrences are considered either in the space that constitutes of the observed quantities, or in an embedding space that is manufactured by time-delayed variables. An alternative approach is proposed here. In the so-called energy-variation analysis, the complexity of an orbit is quantified in terms of the statistics of the constant-speed geodesic condition. Energy-variation analysis requires significantly less operations than state-recurrence analysis, in particular, for multivariate time-series, while numerical experiments demonstrate that the resulting energy-recurrence matrix encodes information that is sufficient for quantifying the complexity of orbits.
The Bessel function J
0 in fractional differential equations
Authors: Funes Jorge Olivares , Kari Elvis Valero , Martin Pablo
Published: December 2021

Spherical Bessel functions have many important applications in engineering, optic and science. In this work, wich is a continuation of the error function in fractional differential equations, it is shown how solve the fractional differential equation

d
α

y

d

x
α

=

j
0

(
x
)
,

y

(
k
)

(
0
)
=
0
,
k
=
0
,

…

m
−
1
,
 
with

m
−
1
<
α
≤
m
,

m
∈
Ν
,

where the nonhomogenous part is the function Bessel spherical J
0(x).
Differential operators and Higher Specht polynomials
Authors: Nonkané Ibrahim , Todjihounde Léonard
Published: December 2021

In this note, we study the action of the rational quantum Calogero-Moser system on polynomials rings. This a continuation of our paper [Ibrahim Nonkan 2021 J. Phys.: Conf. Ser. 1730 012129] in which we deal with the polynomial representation of the ring of invariant differential operators. Using the higher Specht polynomials we give a detailed description of the actions of the Weyl algebra associated with the ring of the symmetric polynomial C[x
1,..., xn]Sn
on the polynomial ring C[x
1,..., xn
]. In fact, we show that its irreducible submodules over the ring of differential operators invariant under the symmetric group are its submodules generated by higher Specht polynomials over the ring of the symmetric polynomials. We end up studying the polynomial representation of the ring of differential operators invariant under the actions of products of symmetric groups by giving the generators of its simple components, thus we give a differential structure to the higher Specht polynomials.
Differential operators and reection group of type Bn
Authors: Nonkané Ibrahim , Latévi Lawson M.
Published: December 2021

In this note, we study the polynomial representation of the quantum Olshanetsky-Perelomov system for a finite reflection group W of type Bn. We endowed the polynomial ring C[x
1,..., xn
] with a structure of module over the Weyl algebra associated with the ring C[x
1,..., xn]W
of invariant polynomials under a reflections group W of type Bn
. Then we study the polynomials representation of the ring of invariant differential operators under the reflections group W. We make use of the theory of representation of groups namely the higher Specht polynomials associated with the reflection group W to yield a decomposition of that structure by providing explicitly the generators of its simple components.
An improved Trapezoidal rule for numerical integration
Authors: Abdulhameed A. F , Memon Q A
Published: December 2021

Numerical Methods have attracted of research community for solving engineering problems. This interest is due to its practicality and the improvement of highspeed calculations done on current century processors. The increase in numerical method tools in engineering software, such as Matlab, is an example of the increased interest. In this paper, we are present a new improved numerical integration method, that is based on the well-known trapezoidal rule. The proposed method gives a great enhancement to the trapezoidal rule and overcomes the issue of the error value when dealing with some higher order functions even when solving for a single interval. After literature review, the proposed system is mathematically explained along with error analysis. Few examples are illustrated to prove improved accuracy of the proposed method over traditional trapezoidal method.
An impedance approach to the response of matter
Authors: Vesely S L , Dolci C A , Dolci SR
Published: December 2021

At the dawn of the research on waveguides the propagation by electrical conduction through transmission lines was compared with the general transmission theory of plane electromagnetic waves. After the invention of lasers we wonder whether the impedance concept can allow a seamless shift from the geometric rendering of received electromagnetic signals to the understanding of simple arguments on power transfer. Perhaps, the impedance concept could help noticing the occurrence of radiation-matter interactions and give hints as to how some phenomena could be enhanced by exposing matter to specific non-ionizing radiations.
RAD_IQ: A free software for characterization of digital X-ray imaging devices based on the novel IEC 62220-1-1:2015 International Standard
Authors: Konstantinidis A , Martini N , Koukou V , Fountos G , Kalyvas N , Valais I , Michail C
Published: December 2021

Characterization of digital X-ray imaging devices is very important because it can be used to measure and compare the performance of detectors used in Diagnostic Radiology. This characterization is usually made through the calculation of Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE). These parameters, especially the DQE, are very important because they quantify the effect of spatial resolution, contrast and noise on Radiographic image quality (IQ). The IEC 62220-1-1:2015 International Standard provides comprehensive guidelines how to capture and analyze X-ray images to characterize digital X-ray detectors. A novel, fast and free MATLAB-based software was developed, named RAD_IQ, to calculate the Signal Transfer Property (STP), perform Noise Component Analysis (NCA), and calculate the parameters MTF, NPS & DQE of X-ray detectors based on the novel IEC 62220-1-1:2015 International Standard for General Radiography and IEC 62220-1-1:2007 for Digital Mammography. Our results were validated against well-established software products used for quantitative image analysis of digital X-ray detectors. The calculated parameters were within 5% difference compared to available software products. The conclusion of our study was that RAD_IQ can be easily used from Medical Physicists, Biomedical Engineers and researchers without any programming experience to characterize the performance of digital X-ray detectors used in Diagnostic Radiology.