bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

AbstractPulsed 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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.