bluuebunny/crossref_metadata_2025 huggingface dataset:
To the 50th Anniversary of Professor V.S. Pavelyev
Authors: Sokolov V O
Published: February 2021

The paper briefly describes the scientific and pedagogical achievements of the Head of the Department of Nanoengineering of Samara National Research University, Doctor of Physical and Mathematical Sciences Vladimir Sergeevich Pavelyev.
Academician Evgeny Pavlovich Velikhov and computer optics
Authors: Kazanskiy N L
Published: February 2021

The article describes the role played by Academician Evgeny P. Velikhov in the development of the scientific direction “computer optics”. It talks about the creation of the journal “Computer Optics”, the establishment of the Research & Education Center “Spectrum”, the support of the Image Processing Systems Institute of the RAS.
Determining parametric functions kinetic constants using the decomposition method
Authors: Ismagilova A S , Khamidullina Z A , Spivak S I
Published: February 2021

The purpose of this work is to automation of the informativity content analysis of kinetic parameters based onde composing a chemical reaction independent route. The software for determining the basis of nonlinear parametric functions of kinetic measurements for the mechanisms of complex chemical reactions is developed and described.
Investigation of the effect of continuous operation of the polymerization process in the presence of Ziegler-Natta catalysts on the molecular characteristics of the product
Authors: Miftakhov E N , Mustafina S A , Mikhailova T A
Published: February 2021

A mathematical model of the process of producing polyisoprene in the presence of various catalytic systems of the Ziegler-Natta type is constructed in the article. When developing a mathematical model, the polycentric nature of the applied catalytic system was taken into account and the modular construction principle was applied, which allows calculations to be made both for the batch mode of the process and for the continuous mode. An analysis was also made of the influence of the hydrodynamic regime on the polymerization rate and the molecular characteristics of the resulting product using the example of a titanium-containing catalyst system.
The probabilistic model of search and detection of ground objects using unmanned aerial vehicles in difficult weather conditions
Authors: Kuznetcov I E , Kuznetcov A A , Baklanov I O , Strashko O V
Published: February 2021

The paper proposes the model of search and detection of ground objects in difficult weather conditions with the use of unmanned aerial vehicles. The model is based on the probabilistic approach and allows assessing the quality of reconnaissance missions taking into account the influence of the most significant meteorological values and weather phenomena.
Catalysts of the catalytic cracking process and development of a fourteen-component kinetic model
Authors: Bikbova G R , Mannanova G I , Gubaydullin I M
Published: February 2021

The catalytic cracking process is specific and depends on several technological factors such as temperature, pressure, type of catalyst and reactor, and contact time. This article presents a review of foreign industrial zeolite-containing catalysts RDM SWM, and Russian microspherical catalyst “Oktifayn”, granular cracking catalysts “adamant”. On the basis of experimental and production data it is possible to conduct mathematical modeling of catalytic cracking process, and to select constants of rates of chemical transformations for each of types of catalysts.
Reorienting nanosatellites to a predefined attitude using angular displacements of movable modules
Authors: Doroshin A V , Eryomenko A V
Published: February 2021

The dynamics of the spatial motion of a nanosatellite with a movable module tilted relative to the main body is considered. Control laws are developed to implement attitude dynamics with suppressing the precession-nutational motion, as well to bringing the nanosatellite into a predefined spatial orientation.
Program for modelling the kinetics of chemical reactions in a cascade of reactors
Authors: Karamova A
Published: February 2021

An algorithm for solving the direct kinetic problem in a cascade of reactors is developed, based on explicit and implicit numerical methods for solving the Cauchy problem. The program is implemented in Borland Delphi environment. There are ability to compile kinetic models of various catalytic processes based on the law of the acting masses in the software package. The software package can be used to simulate the kinetics of an industrial process in a cascade of reactors of ideal mixing of periodic action and ideal displacement.
Application of stochastic calculus for certain classes of quantum models
Authors: Pavelev A , Semin V
Published: February 2021

In this work, stochastic calculus is applied for describing open quantum systems. The suggested approach is based on a modified stochastic Schroedinger equation. We apply the approach to investigate a qubit relaxation in Markovian and non-Markovian regimes.
Using ROC analysis to confirm an algorithmically established diagnosis of lichen planus
Authors: Serikova E , Kalaev V , Serikova O
Published: February 2021

The use of ROC analysis allowed the authors to determine cytogenetic criteria to confirm the diagnosis of lichen planus, obtained by selecting the most informative features and interpreting the micronucleus test in buccal epithelium, calculating their critical values, sensitivity and specificity for use as diagnostic tests. An increase in the number of cells with micronuclei in the lesion of lichen planus is a sign of genetic instability, which can trigger the process of their malignancy. Recognition of nuclear aberrations against the background of nuclear destruction makes it possible to diagnose lichen planus in patients).
Criteria for spin instability based on the node distribution in Trace-transform of the SHS combustion wave chronogram
Authors: Grigoryevskaya A , Gulyaev P , Jordan V , Shmakov I
Published: February 2021

The article presents the results of the Trace analysis of three types of experimental chronograms of the SHS combustion wave in ignition, extinction, and stable propagation modes. It is shown that the use of the differential chronoscopy (DCS) method allows one to reliably determine the moment of occurrence of the spin instability of the SHS wave by the presence of local maxima of the T-functional, when the trace line exactly coincides with the image of the combustion wave front on the DCS map. It was found that in the stable spin combustion mode, the DCS map is a set of periodic isoclines, and this leads to the appearance of point nodes in the 2D image of the Trace transform. As a criterion for recognizing spin instability, we selected the feature of the appearance of local maxima in the central transverse region of the Trace transform spectrum. It is concluded that spin instability is characteristic of the transition from thermal to diffusion instability in the presence of a hysteretic dependence of the burning rate on temperature.
Algorithms of direct simulation of chemical reaction under conditions of uncertainty of initial data
Authors: Zigangirova D R , Mustafina S A
Published: February 2021

Accuracy of measurement of initial data is important in simulation of chemical processes. Distortion of the original parameters can have a significant impact on the result of calculations. In addition to this error, there is also the error of the chosen method of solving the problem. In this article discusses the methods of interval calculations, their using for measurement of initial data and determination of errors in solving problems. Algorithms were implemented in Pascal programming language in Pascal ABC.NET development environment, visualization of solution was obtained with using Mathcad system.
Mathematical modelling of heating features of a cylindrical surface under plasma deposition
Authors: Bogdanovich V I , Giorbelidze M G
Published: February 2021

Mathematical model for temperature determination in a system ‘coating – base’ under plasma deposition of a powder material on the internal cylindrical surface has been developed. Mathematical model takes into account transformation of Gauss heat source, relative motion velocity of a plasmatron, and an angle of a plasma jet relative to the deposition surface. Effect of process variables of deposition on the process thermal stress and quality of plasma coatings has been analyzed.
Hydrodynamics in counterflow cooling tower with corrugated inclined contact elements
Authors: Dmitriev A V , Madyshev I N , Khafizova A I , Nikolaev A N
Published: February 2021

Packing for water cooling at counterflow motion of gas and liquid phases has designed by authors of present paper. Such packing differs from other devices in that it is not needs the additional redistributive devices installation, has an opportunity of arbitrary distribution of liquid in apparatus working area due to using of inclined corrugated contact elements. Assessment calculations for packing operation modes determination which purpose is to minimize of dead spaces volume and to increase a circulating water cooling efficiency are performed in this study.
About an algorithm for modeling the isoprene polymerization process in the cascade of reactors using the Monte Carlo method
Authors: Mikhailova T A , Miftakhov E N , Mikhailov V A , Mustafina S I
Published: February 2021

The article describes an algorithm for modeling the isoprene polymerization process based on the Monte Carlo method. The algorithm can be used to simulate polymerization processes carried out in batch or continuous mode. The possible polycentricity of the catalyst used is also taken into account. The model is based on this algorithm makes it possible to study the properties of the polymerization product and calculate the molecular weight distribution for different points in time.
Modelling of ceramic coatings grow during Arc-PVD deposition
Authors: Chernogor A V , Blinkov I V , Volkhonskiy A O
Published: February 2021

This paper presents the results of modeling the growth of ceramic coatings obtained by the kinetic Monte Carlo method. In the considered model, the possibility of forming misoriented grains in the direction of coating growth and in the plane of coating is realized. To verify the model, three coatings of different compositions were prepared, and their structure and composition was studied by TEM and EDS.
Performance computing of an open cycle micro gas turbine powerplant using data aided modeling and simulation
Authors: Thomas Jayachandran A V , Tkachenko A Y , Omar H H , Krishnakumar A
Published: February 2021

In this paper the study of the thermodynamic performance for a 6kW micro gas turbine power plant has been optimized by considering Air-fuel ratio at various altitudes along with fuel inlet temperature. The parametric analysis was performed to improve the overall efficiency of the power plant to obtain the required power needed by a multi-copter. The research deals with parametric optimization for determining realistic and practical combinations for improving the specific fuel consumption and overall efficiency of the Micro gas turbine power plant. The use of recuperators has not been beneficial for the micro gas turbine power system due to the increase in the total volume and weight of the engine. The fuel inventory should be decreased significantly to justify the addition of a recuperator system. The addition of heat exchangers improves the Specific fuel consumption that results in environmental friendly micro gas turbine engines. The result of this work helps to develop and design the micro gas turbine with high efficiency and at the optimized output. A model for a 6 kW micro gas turbine power plant was optimized for the application of primary power units for multi-copter or drones at low altitude conditions. To validate the model, JET CAT PHT3 shaft turbine design parameters were used and the results are compared with the experimental tests on this engine.
Modeling and parametric optimization for a solar-powered closed-cycle micro gas turbine for space applications
Authors: Thomas Jayachandran A V , Tkachenko A Y , Omar H H , Krishnakumar A
Published: February 2021

The research describes the theory design and the modeling of a closed cycle micro gas turbine power plant (CMGTP). A computer simulation model in ASTRA is used to model specifically for this cycle. The software model has been tested for various configurations of gas turbines. For the commercial viability and success of the CMGTP, it should have significant operational feasibility. The working fluid properties play a vital role. The research is a feasibility study to examine the technology for Brayton-cycle based solar thermal power plants and to optimize the model in comparison with Solar array photovoltaic cells to increase the power density by increasing the power generated per unit solar-collector area. A mathematical model for CMGTP was de-signed to power satellites in space environments. The goal is to provide electricity from a parabolic mirror acting as a heat source that is collected by pointing at the sun. The Closed Brayton Cycle power was simulated to produce an output of 6 kW at the generator terminal. The heat source generated from the sun was considered to be around 750 K to 1250 K. The vacuum at the space radiation environment was considered to be 200 K acting as a coolant sink. The optimization of the power plant priorities is followed as High thermal-to-electric efficiency, Low mass, and volume. Computer simulation for thermodynamic analysis was performed on the selection of the working fluids, Brayton cycle design parameters, a heat exchanger (heating and cooling temperatures) that meets the best criteria. A system-level tradeoff study was performed to optimize for achieving target functions for critical factors. The CMGTP consists of a centrifugal compressor, a radial in-flow turbine on a single shaft powering a two-pole permanent magnet alternator.
Nonlinear dynamics of rectangular nano-shells
Authors: Krysko V A
Published: February 2021

Mathematical model of non-linear vibrations of shallow, elastic, isotropic nano-shells with rectangular base subjected to transverse sign-variable load are constructed. Based on Kirchhoff-Love thin shell theory with von Kármán nonlinear strains and the modified couple stress theory (MCST), size-dependent governing equations and corresponding boundary conditions are established through Hamilton’s principle. The governing PDEs are reduced to ODEs by the second-order Finite Difference Method (FDM). The obtained system of equations is solved by Runge–Kutta methods of second order accuracy. The Cauchy problem is solved by the Runge–Kutta fourth-order method. We analyzed the convergence of these solutions depending on the step of integration over time and spatial coordinate. It was revealed, that taking into account nano-effects increases area of harmonic vibrations and leads to the appearance of as chaotic and hyperchaotic vibrations. The carried out numerical experiment shows, that the transition of vibrations from harmonic to chaotic follows to Feigenbaum’s scenario. In particular, to analyze the character type of vibration computation of largest Lyapunov exponents are employed. We found that hyperchaotic vibrations are characterized by two positive Lyapunov exponents and chaotic vibration by one positive Lyapunov exponent. For nano-shells, this phenomenon was discovered for the first time. Lyapunov exponents spectra estimated by different algorithms, including Wolf’s, Rosenstein’s, Kantz’s, and Sawada. Numerical examples of the theoretical investigations are given.
Numerical simulation of bottom topography transformation taking into account the coastal shore protection structures
Authors: Sukhinov A I , Protsenko E A , Sidoryakina V V , Protsenko S V
Published: February 2021

The article presents the results of studies and modeling the dynamics of nonlinear processes of sediment transport and the diagnostics of changes in shallow water relief, taking into account underwater structures that are widely used for coastal protection. The study of these processes was carried out on the basis of 2D model of sediment transport and 3D model of wave hydrodynamics, taking into account the geometry of the bottom topography and the function of elevating the level of the aquatic environment. A discrete model of sediment transport is obtained by approximating the corresponding linearized continuous model. Particular attention is paid to the creation of effective software for conducting hydrodynamic computational experiments. The developed software package allows predicting the dynamics of bottom surface behavior, the appearance of marine braids and ridges, their growth and transformation.
Parameter identification algorithm for convection-diffusion transport model
Authors: Kuvshinova A N , Tsyganov A V , Tsyganova Yu V , Tapia Garza H R
Published: February 2021

This paper considers an application of gradient-type optimization algorithm for solving the problem of convection velocity and diffusion coefficient identification in the convection-diffusion transport model. A solution is obtained by the means of numerical minimization of the parameter identification criterion for a discrete linear stochastic model in state space. The log-likelihood function is used as the identification criterion. Numerical experiments were conducted to confirm the efficiency of the proposed solution.
Critical traveling wave solution in the Meinhardt type model
Authors: Sobolev V A
Published: February 2021

The traveling waves problem for the singularly perturbed semilinear parabolic equations is considered in the paper. It is shown that the corresponding problem for a singularly perturbed ODE system can be reduced to a certain problem of lower dimension using a splitting transformation based on the technique of slow and fast integral manifolds. The Meinhardt model is considered as an example.
Square-root filtering for discrete-time systems with multiplicative and additive noises
Authors: Kureneva T N , Tsyganov A V , Tsyganova Yu V , Volkova N A
Published: February 2021

The paper addresses the problem of constructing numerically efficient linear filtering algorithms for discrete-time linear stochastic systems with multiplicative and additive noises. A new square-root covariance algorithm for optimal linear filtering is proposed. We demonstrate that the developed algorithm is algebraically equivalent to the standard covariance filter. Also it has the improved computational properties inherent to all square-root algorithms. The results of numerical experiments confirming the operability of the proposed algorithm are presented.
Overview and perspectives on metric-affine gravity
Authors: Belarbi O A , Meziane A
Published: February 2021

The main purpose of this work is to give an overview of a generalization of the theory of general relativity, namely metric-affine gravity. We rederive an expression for the Lie derivative of the metric in the case of metric-affine theory and discuss some consequences of such an expression. As a gauge theory of gravitation it may be considered as an upshot of a gauging procedure of the general affine group, or its double covering. A historical approach of such a theory is also contained including the key results. One concludes with some perspectives on the calculation of topological observables in that theory viewed as topological gravity theory.
Homogeneously modified special relativity applications for UHECR and neutrino oscillations
Authors: Miramonti L. , Antonelli V. , Torri M.D.C.
Published: February 2021

One of the key open questions in fundamental physics concerns the supposed quantum structure of spacetime. New physical effects are expected as residual evidence of a more fundamental theory of nature. In this fundamental theory the underlying physical symmetries could be modified by the quantized structure of geometry. One of the most important symmetries in our description of Physics is Lorentz Invariance (LI). Nowadays LI is at the root of our understanding of nature and underlies its physical description. Even if there is no definitive evidence to sustain departures from this symmetry, there are consistent points indicating that Lorentz Invariance Violation (LIV) can be a consequence of quantum gravity. A critical issue concerns therefore the necessity of testing this fundamental symmetry validity. Ultra High Energy Cosmic Rays (UHECR) and neutrino flavor oscillation are promising physical processes of investigation for LIV, since the high energy involved and the interaction of different particle species.
Dynamic evolution of ionization and recombination processes and ion front acceleration in the presence of nonthermal and trapped electrons
Authors: Bara D , Mahboub M F , Bennaceur-Doumaz D
Published: February 2021

The dynamic evolution of ionization, three-body and radiative recombination processes in high intensity laser ion acceleration mechanisms, has been studied. For that, the expansion of a collisional thin plasma slab in vacuum is modeled using mixture hydrodynamic fluids equations for ions and neutral atoms, in the presence of fast nonthermal and slow trapped electrons, obeying a Cairns-Gurevich distribution. In addition, the characteristics of ion front acceleration and ion gained energy profiles are obtained, for three types of accelerated ions (H
+, C
+ and Al
+). It is proved that, ionization and recombination processes are responsible for the energy transfer between plasma particles. These processes are also strongly influenced by the impact of electron nonthermal phenomena, generated by the interaction of an intense laser pulse with the target. On the other hand, parametric studies have proved that ion energy profiles, maximum electric fields and ion energies at the ion front acceleration are also significantly affected by these phenomena. This study is useful in applications involving the creation of energetic ion beams, such as protontherapy.
A Comparative study by TCAD Simulation for two different planar n-on-p silicon particle detectors with different guard ring implant type
Authors: Oussalah S , Mekheldi M , Filali W , Garoudja E
Published: February 2021

In this paper, we compare two multi-guard ring geometries for n-on-p silicon particle detectors for high luminosity applications. One structure has p-type guard rings while the other has n-type guard rings with p-stop isolation between n+ implants. The pre-irradiation performance of the guard ring structures are studied as a function of oxide charge. It is found that for both structures, there is a value of oxide charge for which the breakdown voltage is maximum. The post-irradiation performance of the structures are evaluated with simulations up to a radiation fluence of 1×10+16 neq/cm2 using an existing three-level trap model for p-type FZ silicon. TCAD simulation has been used to simulate I-V characteristics, charge carrier concentration, electric field, and potential distribution.
The von Neumann boson-antiboson pair creation quantum entanglement entropy in noncommutative Bianchi I space-time
Authors: Ghiti M F , Mebarki N , Aissaoui H
Published: February 2021

The noncommutative Bianchi I curved space-time vierbeins and spin connections are derived. Moreover, a general Klein-Gordon equation up to the second order of the noncommutativity θ paramter and its solutions are presented. As an application within the quantum field theory approach using Bogoliubov transformations, the von Neumann boson-antiboson pair creation quantum entanglement entropy is studied. It is shown that its behavior is strongly dependent on the value of the noncommutativity θ parameter, k⊥ modes frequencies and the structure of the curved Bianchi I space-time. various discussions of the obtained numerical results are presented.
On the pseudo hermiticity and q-deformation
Authors: Moulla H , Mebarki N , Leghrib I
Published: February 2021

The non hermiticity of the Hamiltonian is shown to be generated from the q-deformation of the algebra. As an example the q-deformed harmonic oscillator is investigated within the leading order approximation in the pseudo Hermitian perturbation theory. A generalized form of the metric is constructed. The spectrum as well as eigenstates of the system are derived explicitly.. Some applications and illustrations in q-deformed quantum statistical mechanics are also discussed.
Effect of curvature on the nucleation of quark-gluon plasma droplets from a hadronic gas
Authors: Mezouar K , El Djoudi A Ait
Published: February 2021

We study the nucleation of quark-gluon plasma (QGP) droplets in a hadronic gas phase (HG). This process is driven by statistical fluctuations which are determined by the difference in free energy in the QGP and hadronic gas phases. We investigate this difference in free energy in two cases; when considering the curvature term additionally to the volume term in the density of states of particles constituting the QGP and without considering it, and this for the color singlet SU(3) representation of the QGP. The behavior of the obtained change in free energy is examined with varying radius of the QGP droplet, at vanishing chemical potential, in the two cases. The obtained results with and without the curvature contribution in the density of states are compared, and the effect of the curvature term on the nucleation of QGP droplets from a hadronic gas is analyzed.
The exact solution of a three-body problem of Calogero type in one dimension by the SUSY-QM and SGA methods
Authors: Sekhane I
Published: February 2021

Analytic expressions of the eigenvalues for a non-relativistic Hamiltonian of a three-body problem of the Calogero type can be derived using both the well known method of supersymmetric quantum mechanics SUSY-QM and an independent group theoretic method, namely the spectrum generating algebra SGA. We demonstrate the equivalence of the two methods by developing an algebraic framework through the shape invariance SI property with a change of parameters which involves nonlinear extensions of Lie Algebra.
On the super quantum information
Authors: Khemakhmia A , Mebarki N
Published: February 2021

A superqubit is a three dimensional super vector belonging to uOSP(1/2) super group. And considered as a super symmetric generalized qubit. To see how superqubits properties can be exploited in the field of the quantum computing, we propose some algorithms in order to perform the super teleportation. implementation and technologies. Using superqubit circuits will be an open field of research.
Investigating the similarity between the behavior of the order parameter derivatives and that of cumulants of the probability density for the thermal deconfining phase transition at zero chemical potential
Authors: Djida R , El Djoudi A Ait
Published: February 2021

In this work, we study the temperature driven deconfining phase transition, at zero chemical potential, in a statistical way, by means of the probability distribution of finding the mixed hadronic gas-QGP phase system in a finite volume, in a specific state defined by a parameter lying between 0 and 1, whose mean value represents the order parameter of the studied system. We calculate mean values of other characteristic quantities, called response functions, which are mainly the second, third and fourth cumulants of the probability distribution representing the variance, skewness and kurtosis respectively, as well as the three first thermal derivatives of the order parameter. Integral expressions are obtained for all these quantities, and their evaluation is done numerically. The such obtained results are adequately translated into graphs, illustrating the variations of the response functions with temperature, for various volumes. By examining their behavior, we notice a striking similarity between the behavior of the order parameter derivative and that of the cumulant, at the same order. We investigate this similarity and try to deeply analyze it, to obtain some important features characterizing the occurring deconfining phase transition.
Personalized Prognosis of Oncosurgical Patients Using Standard Tool Microsoft Access
Authors: Udalov Yuri D. , Vasilyeva Irina V. , Gordienko Alexander V. , Popugaev Konstantin A.
Published: February 2021

The most common treatment for oncological diseases is using of surgery. Despite successful methods of surgery, the problem of a personalized prediction of the outcome of hospitalization is an important and fundamental problem in the treatment of a noncosurgical patient with five or more concomitant diseases. This is due to the fact that at present the choice of an unified approach to the decision to conduct a planned surgical intervention in the case of oncological pathology with appropriate recommendations puts the physician before a difficult choice of treatment tactics for each case separately. There are many prognostic models, both implemented and not implemented in the form of various computer and mobile applications that allowedphysician to assess the severity of the patient’s condition and predict the outcome of treatment. Therefore, to support the physician of a medical decision, simple and accessible tools are needed, allowing divide patients according to individual selection of the treatment regimen. Nevertheless, the introduction of specific models for predicting therapeutic measures (for example, surgical intervention) in patients, in particular elderly patients, in clinical practice often remains at the level of basic research and is used only in a few clinics related to that studies.The purpose of our work is to implement a decision rule as the Microsoft Access software, which allowed ranking patients with oncological diseases by the probability of lethal outcome before surgical intervention.The software implementation methodology was implemented using elements of the standard Access database.The result of our research was the implementation of a decision rule in the form of Microsoft Access software Oncoprognosis 1.0, which allows physician to rank oncosurgical patients according to the likelihood of death in oncology.
Information Extraction Research Review
Authors: Zhu Dengyun , Guo Qi , Zhang Dongjiao , Wan Fucheng
Published: February 2021

Information extraction is to extract the required specific entity, event, relationship and other information from a large number of texts and store it in a structured form, which occupies an important position in the field of natural language. Information extraction helps people get the information they need efficiently, avoids a lot of complicated work, and saves manpower and material resources. In this paper, named entity recognition and so on are described and summarized in detail, as well as the prospect of information extraction.
Prediction of Internet User’s Purchase Behavior Based on Mixed kernel SVM Model
Authors: Hu Wen , Shi Yuxue
Published: February 2021

In order to better predict the purchase behavior of online consumers and improve the purchase conversion rate of e-commerce companies, a model of consumer purchase intention prediction based on mixed kernel function support vector machine is proposed. In the research, the prediction model of consumer purchase intention is designed as a two-classification problem, and the feature selection algorithm mRMR is used to obtain the ranking of features, seeking to obtain better or similar classification results when choosing fewer features. On its basis, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of the model. Experiments show that, to a certain extent, the constructed mixed kernel function can effectively improve the classification effect of SVM.
A Rapid Ultrasound Vascular Disease Screening Method using PauTa Criterion
Authors: Xiao Huiyue , Zhang Yi , Liu Xin , Yin Hao , Liu Paul , Liu Dong C.
Published: February 2021

Pulsed Wave Doppler (PW) is a traditional ultrasound technique used for the diagnosis of vascular diseases. The conventional diagnostic method is mainly based on hemodynamic parameters obtained from the PW spectrum. However, it relies on clinical observation and medical experience through lots of patient data investigation and analysis. The collected patient data are varied by different ultrasound equipment, detection regions and operation techniques, resulting in different image styles, which decreases the application and generality of the conventional method. And this method also has a strong dependence on patients’ data, especially on negative samples. Thus this paper proposes a rapid disease screening method, named as PauTa Criterion, which is based on statistical distribution characteristics for screening out anomalous targets. The proposed rapid screening method is based on multiple hemodynamic parameters to detect the outliers that are different from healthy samples. Compared with the conventional methods, the proposed method does not rely on a fixed or single ultrasound system and has low sensitivity to system noise. The experimental results show that the proposed method reaches a high accuracy of 93.14%, which is at least 20% higher than existing clustering methods, K-Means and Support Vector Machine (SVM). Accordingly, high accuracy and fast convergence makes the prospect of the proposed method to be used for rapid disease screening possible.
A Short Review of the Application of Machine Learning Methods in Smart Airports
Authors: Huang Hailong , Zhu Jinfu
Published: February 2021

Machine learning has influenced the modern transportation in many aspects, such as it could help construct ‘smart airports’ along with big data. Many researchers have discussed a lot of relevant topics in this area. This paper gives a relevant short review, indicating that there are mainly 4 issues which are under the concept of machine learning in the construction of smart airports in recent times. The issues are flight delays, airport environment, operation management of airport, safety of airport. The researches of the 4 issues have become the mainstream for the studies on smart airports.
RU-Net for Heart Segmentation from CXR
Authors: Lyu Yu , Huo Wei-Liang , Tian Xiao-Lin
Published: February 2021

Cardiovascular disease is one of the top causes of death in the world. In order to release heavy workload for doctor, automated segmentation methods using deep learning are proposed by researchers. Due to limitation of medical images, we proposed a novel model RU-Net based on the combination of U-Net and Residual Network for heart segmentation. We replaced Res path from direct skip connection from encoder to decoder. We use Jaccard similarity coefficient to compare the result of our method and U-Net with public dataset called Japanese Society of Radiological Technology (JSRT). The experiment result demonstrates the accuracy of our method.
Convolution Neural Network Application in the Simultaneous Detection of Gender and Variety of Silkworm (Bombyx mori) Cocoons
Authors: Dai Fen , Wang Xianyan , Zhong Yangsheng , Zhong Suyuan , Chen Chuhan
Published: February 2021

Convolution neural network (CNN) has been widely studied in the field of computer vision with good results, and a lot of research is still needed to show its application effect in the near-infrared spectroscopy with 1-D input data and small sample set. In this paper, the near-infrared diffuse transmission spectra of 2386 silkworm (Bombyx mori) cocoons from the 4th day of cocooning to the 13th day before turning into moths were collected. After the mean center preprocessing, CNN, SVM and LDA were used to model and analyze. Experimental results showed that, with the convolution kernel width 100, the convolution kernel num 16, and the stride 50, the good generalization effect of CNN model can be achieved when the simple structure of 6 layers without pooling layer was adopted. For each day, the gender prediction accuracy of cocoons is more than 90% and the highest accuracy is 100% on the 6th day with optimal model CNN. For each day, the variety prediction accuracy of cocoons is more than 98% and the highest accuracy is 100% with optimal model LDA. There is no significant correlation between pupa age and the gender and variety detection accuracy of silkworm cocoons. This can help broaden the pupa gender identification time in the actual production of silkworm egg farms. In the application of simultaneous identification of gender and variety, CNN model has the highest accuracy of 94%, LDA model has the medium accuracy of 92.5%, and SVM model has the lowest accuracy of 89.5%.
Analysis and Research of Weibo Public Opinion Based on Text
Authors: Zhu Yaling , Li Xiangwei , Wang Juan
Published: February 2021

With the rapid development of social networks, social platforms such as Weibo and WeChat have become important places for the development and evolution of public opinion events. Therefore, analyze the trend of online public opinions through social platforms. Managers can analyze user preferences and grasp user needs, and help decision-makers to better improve their ability to deal with emergencies. The paper uses the python automatically to get the data from the Weibo. Using the Xunfei sentiment analysis API to identify the emotional polarity, and result feedback to the user. By using the Weibo emotional tendency analysis, the government can track social conditions and public opinions, study and judge online public opinions, guide the direction of public opinions and resolve crisis public opinions.
The Application of AMT Based on 3D Modelling Technology in Uranium Exploration in Huayangchuan Area, Shaanxi Province
Authors: Bo Li , Junlin Ran , Kuanhong Liu , Huiming Yao , Hong Tu
Published: February 2021

The AMT (Audio-frequency Magnetotellurics) has been carried out in the exploration of uranium deposits in Huayangchuan area, Shaanxi Province. The results show that AMT can effectively detect the scale and occurrence of tectonic fractured zones. It provides an effective technical methods for the uranium deposits in Huayangchuan area to search for deep and peripheral exploration.
Research on Safety Evaluation Model of Construction Enterprise Based on Quartet Game
Authors: Yang Xingang , Du Tingting , Wang Qiquan
Published: February 2021

Safety evaluation of construction enterprises is an important prerequisite for building accident prevention and emergency response. In the process of evaluating construction enterprises’ safety, we must consider not only the enterprises themselves, but also many other influencing factors. Therefore, we constructed a quadripartite game model of government departments, construction enterprises, employees and trade union organizations, and put forward relevant suggestions to improve the safety situation of construction enterprises. On the basis of fully considering various factors, we give a safety evaluation model of construction enterprises based on quadripartite game, and make an example evaluation and analysis.
Computer Simulation Research on Flow Field of SRM High Altitude Simulation Test
Authors: Jia Dongyi , Li Zhuo
Published: February 2021

The simulation test of passive ejection type high-altitude solid rocket motor (SRM) was simulated by computer. For SRM passive ejector type high-altitude test, the tempering in the process of engine ignition and flameout poses a serious threat to the nozzle of the engine test device and circuit arrangement in the upper compartment. Using the N-S equation and Spalart-Allmaras model: numerical simulation on the flow structure of engine pressurize, decompression and stratochamber air phase in the testing process, and flow field of the diffuser and the cabin altitude simulation, analyzing the flow field structure of high-altitude experiment stages. The results showed the rough coincidence between the simulation curve and the measured data, with slight difference at the initial stage of air supply, the measured data and the simulation data reach the overall high degree of coincidence. During the process of building a compression and decompression, the adiabatic measures should be taken to prevent high temperature gas from damaging the engine, especially the nozzle and the head ring, in addition, the reasonable design of the nozzle contour surface can control gas separation tempering, reducing the influence caused by tempering. Stability of the flow field in the high altitude chamber of the pressure will not affect the engine.
Problems and Countermeasures of Enterprise Internal Control in Big Data Environment
Authors: Li Donghui
Published: February 2021

The rapid development of modern society, the flow of information has accelerated the communication between people, and big data is the product of this background. Big data technology has also begun to be widely used in enterprises, which will inevitably bring a major change. The internal control of an enterprise, as the basis of all the management mechanisms of the enterprise and an important means for determining whether an enterprise can survive and develop in the fierce market competition, has also ushered in a revolution because of big data. Therefore, in the context of big data, how to achieve the ultimate goal of internal control and the risk prevention of internal control has become the subject we need to study.
Load Distribution Coefficient of Node of Lattice Beam Based on Two-Parameter Elastic Foundation Model
Authors: Zhang Taiyue
Published: February 2021

According to the force characteristic of lattice beam, used the Two-parameter elastic foundation model to deduce the answer of internal forces of concentrated force on the finite-length beam, and calculate load distribution coefficient of node, then get the internal forces of lattice beam, used the analytical solution combined with practical engineering, and compared with numerical solution of simulation of ABAQUS finite element software, to verify the correctness of theoretical solution, and analyze its deficiency.
Research on Cyber Security Defense and Protection in Power Industry
Authors: Chen Zhiyu , Guo Yonghe , Bai Dongxia , Wang Jiaxin , Dong Yaozhong , Qian Shengqi , Lu Teng , Xing Hairui
Published: February 2021

The power information network is a significant part of national key information infrastructure, as well as the core promoting force to guarantee the strategic development of energy internet. Due to its correlative characteristics in industrial control network, the internet and IoT, superadd a large of nodes and data sensitivity, the evolving network attack technology has put forward new requirements and challenges to its security protection system, which also hinders the overall interconnecting and interworking of energy internet to a certain extent. In order to improve the network security capability of full-service power network under the energy internet environment, a power information security framework based on cloud service was proposed to improve the safety and reliability, build an end-to-end electronic authentication mechanism and security management mode of strong data interworking, finally realize the life cycle data protection, trusted identity management and reliable electronic voucher application, meet the rapid development of the energy internet and escort the new digital economic of the power industry.
The Design and Load Experiment Study on Corbel of Moving Sinking hanging Scaffold for Ultra-deep Shaft
Authors: Liu Jie , Long Zhi Yang
Published: February 2021

Aiming at the difficulty of suspending the hanging scaffold of ultra-deep shafts, the corbel suspension device was designed by analyzing the needs of the moving type sinking hanging scaffold, and the strength check calculation was carried out to theoretically verify that the corbel can withstand the pressure of the sinking hanging scaffold. At the same time, through the no-load and heavy-load experiment of the moving type sinking hanging scaffold, the working status, force and overall load of each corbel of the moving type sinking hanging scaffold were monitored in real time. According to the experiment, it is concluded that the corbels can meet the conditions of use under the most unfavorable working conditions, which further improves the structural design theory of the sinking hanging scaffold and ensures the safe construction of the moving type sinking hanging scaffold.
Research on Generalized Multimodal Transport Cost Assignment Model Based on Super Transportation Network
Authors: Zhang Yonghong
Published: February 2021

In view of the problem of independent demand prediction and lack of overall integration in the current comprehensive transportation spatial planning, this research establishes a unified research framework by setting up a super transportation network, based on GIS platform in consideration of multi-modal transport demands in sectors such as railway, highway, waterway, civil aviation, postal service and pipeline. The county-level comprehensive traffic zones are established, incorporating various demands of each transport mode. This paper innovates the method of modal split prediction, via the use of passenger and cargo transportation functions to perform multimodal generalized cost model prediction distribution on the super transportation network, thus providing technical support for the integration of comprehensive transportation planning.
Network Representation Learning Algorithm Combined with Node Text Information
Authors: Wang Rui , Liu Yu , Chen Jiawang
Published: February 2021

In a network data analysis task, network representation learning play an important role. It can obtain a low-dimensional representative vector from high dimensional features of nodes which will promote the efficiency of downstream analysis task. Many algorithms mainly based on the structure information of the network but for a complex network, there is a lot kinds of feature information available for representation learning which has an important impact on network data analysis task. Therefore, we propose a network representation learning algorithm that combines node text information. Before our algorithm, we encode the information of the nodes including structure and text, and the strategy of fusion is adopted in advance which splice structure and text information. And then we feed the splicing results into the neural network which is a multi-layer feedforward neural network with a tower structure to learn the nonlinear structure information of complex networks. Finally, we design the structure loss function that preserve structure similarity and text loss function that preserve text information respectively. And we use the joint training to make two aspects information interact continuously. We conduct experiment to evaluate our algorithm. The results on two real word networks show our algorithm has better performance compared with traditional algorithms.
A Representation Learning Algorithm Preserving Structure and Attribute Proximity
Authors: Liu Yu , Wang Rui , Chen Jiawang
Published: February 2021

Representation learning is the application of data mining on complex networks, which extracts high-dimensional information from nodes to form a low-dimensional representation vector, and offers a better input to downstream application. So it has attracted many researchers’ attention recently. In a complex network, there are many kinds of node information, including the attribute information and structure information which are of great significance for data mining because they determine the nature of the node. However, the limitation of popular methods is that only the structure information between the node is considered, the rich high-dimensional attribute information of nodes has been ignored. The relationship between these attribute information of nodes in complex network is also important reference in the process of node representation learning. To address this problem, we propose an algorithm that uses the autoenconder to extract features based on fusion with node structure features and attribute features, and gets a more representative node representation vector. We apply the new algorithm on different datasets compared with popular baseline algorithms. The results show that the method we proposed is effective and it has good performance in visualization and node classification.