bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visual reasoning and the perception of forms
Authors: Vesely S L , Vesely A A , Dolci C A , Dolci S R 
Published: February 2021

Abstract
Whenever a new device enables our senses to access an uncharted sensible world, our experience needs to be widened to be able to embrace it. Many animals don’t recognize themselves in mirrors. Thus, mirrors found in ancient Egyptian tombs bear witness to a device that involved a widening of human experience. While by then reflectors were commonly believed to hold the spirit of their beholder, they also provided the motivating force for use of geometry as a logical framework, rather than the form of the outer world. Euclid of Alexandria conceived of geometric constructions and their rules as the connecting link between visual world and hypothetical-deductive reasoning. Yet, he didn’t have a clue about receivers. In our view the problem of linking received information in an image format to a mathematical space cannot be solved once and for all, but rather needs to be posed and understood afresh once in a while. All the more so in an information and telecommunication era, when the techniques of acquisition and rendering of visual information have been extended well beyond the domain of optical instruments, and the language of mathematics has advanced to a different level of proficiency.
Optimal Control and Stability Analysis of Nonlinear Control-Affine Systems
Authors: Bagdasaryan Armen 
Published: February 2021

Abstract
In this paper we will discuss the problems of optimal control and stabilization for nonlinear control-affine systems of the form

x

˙

=
A
(
x
)
+
B
(
x
)
u

where

x
=
x
(
t
)
,
x
∈

R

n

,
u
∈
R
,

|

u

|

≤
1

and vector functions A(x), B(x) are assumed to be smooth in the domain D ⊂ ℝ
n
, 0 ∈
D, A(0) = 0. We give an in-depth analysis of optimal control problems for nonlinear dynamical systems and then consider for the above systems the problem of synthesis of continuous control u = u(x), u(0) = 0, that stabilizes the system at the equilibrium point (x, u) = (0, 0). The solution to the problem is based on the transformation of the system to canonical form, and on nonlinear stabilization of the system.
Remastering the imperfect home-made CT projections data for further reconstruction
Authors: Kussainov Arman S , Saduev Nurzhan O 
Published: February 2021

Abstract
We developed and implemented a few strategies to recover the faulty, randomly shifted, off-axis rotation sequence of projections images for the home-made computed tomography. Features detection, homography and other image transformation and processing tools from the open-source free and non-free OpenCV libraries in C++ were used. The developed methods, routines and implemented strategies could be collected into the standalone library for any home-made CT software packages.
Explanation of Light Deflection, Precession of Mercury’s Perihelion, Gravitational Red Shift and Rotation Curves in Galaxies, by using General Relativity or equivalent Generalized Scalar Gravitational Potential, according to Special Relativity and Newtonian Physics
Authors: Vossos Spyridon , Vossos Elias , Massouros Christos G. 
Published: February 2021

Abstract
The development of Geometric theories of gravitation and the application of the Dynamics of General Relativity (GR) is the mainstream approach of gravitational field. Besides, the Generalized Special Relativity (GSR) contains the fundamental parameter (ξ
I) of Theories of Physics (TPs). Thus, it expresses at the same time Newtonian Physics (NPs) for ξ
I→ 0 and Special Relativity (SR) for ξ
I=1. Moreover, the weak Equivalence Principle (EP) in the context of GSR, has the interpretation: m
G=m, where m
G and m are the gravitational mass and the inertial rest mass, respectively. In this paper, we bridge GR with GSR. This is achieved, by using a GSR-Lagrangian, which contains the corresponding GR-proper time. Thus, we obtain a new central scalar GSR-gravitational generalized potential V=V(k,l,r,r_dot,ϕ
_dot), where k=k(ξ
I), l=l(ξ
I), r is the distance from the center of gravity and r_dot, ϕ
_dot are the radial and angular velocity, respectively. The replacement k=1 and l=ξ
I
2 makes the above GSR-potential equivalent to the original Schwarzschild Metric (SM). Thus, it explains the Precession of Mercury’s Perihelion (PMP), Gravitational Deflection of Light (GDL), Gravitational Red Shift (GRS) etc, by using SR and/or NPs. The procedure described in this paper can be applied to any other GR-spacetime metric, in order to find out the corresponding GSR-gravitational potential. So, we also use the GR-proper time of the 3rd Generalized Schwarzschild Metric (3GSM) and we obtain the central scalar GSR-gravitational potential V=V(a,k,l,r_dot,ϕ
_dot), where a=a(r). The combination of the above with MOND interpolating functions, or distributions of Dark Matter (DM) in galaxies, provides the functions corresponding a=a(r). Thus, we obtain a new GSR-Gravitational field, which explains the PMP, GDL, GRS as well as the Rotation Curves in Galaxies, eliminating the corresponding DM.
On regular and irregular movement of cylinder colliding with a moving belt
Authors: Lampart M , Zapoměl J 
Published: February 2021

Abstract
Conveyors and moving belts are frequently used in the field of mechanical engineering. In many operating regimes they are subjected to impact loading, which can induce irregular motion and undesirable behaviour of the working machine. This paper focuses on the impacts between an impact body (the cylinder in our case) and a moving belt. Results of the simulations show that different combinations of the system parameters produce a high complexity of device motion. The bifurcation analysis together with outputs of the 0-1 test for chaos and sample entropy indicates different movement regions. The performed analysis elucidated more about the properties and behaviour of mechanical systems with strong nonlinearities such as impacts and dry friction.
Computer simulation in proton therapy
Authors: Echkina E. , Guzminova N. 
Published: February 2021

Abstract
The ionising radiation as a method of cancer treatment has a long history. Any types of radiation have been employed to achieve control of tumour viability such as a’low’ linear energy transfer (LET) beam of photons, two’high’ LET unmodified and spread-out Bragg peak (SOBP) beams of protons. Per the end of 2018, about 190036 patients have been treated with protons [1), 93 facilities in clinical operation worldwide in April 2020 (2). The unattainable goal so far is the creation and implementation of such a treatment plan in which the target volume receives 100 % of the prescribed dose and healthy surrounding tissue 0%. The goal of modern science to find ways to ”optimised” treatment plan especially in childhood cancer, where the preservation of healthy tissue surrounding the tumour is especially important. In our work we presented the results of a calculated experiment of the interaction of a laser impulse with various targets and showed the dependence of energy distribution from the target types.
Estimation of Parameters for Non-Equilibrium Phase Transitions during the Flow of Oil and Gas Mixtures
Authors: Indrupskiy I M , Cherneva N Yu 
Published: February 2021

Abstract
Problems of unsteady gas-liquid flows in wellbores with phase transitions are common for hydrocarbon production and well drilling. Typically, flow in wellbores is sufficiently fast which requires taking into account the non-equilibrium nature of phase transitions. The set of equations describing conservation of mass for components and momentum conservation for the mixture is supplemented by the relaxation equation for concentration of gas dissolved in the liquid. It is known that the characteristic times of gas evolution from the liquid and gas dissolution in the liquid differ significantly and depend on fluid properties, thermobaric conditions, and the flow pattern. Therefore, obtaining estimates of relaxation times for real flows turns to be a difficult problem. In this study, we propose a method for estimating the characteristic relaxation times for gas evolution and dissolution during the gas-liquid flow in a well. The method combines the solution of the convective diffusion equation for the growth/collapse of a vapor bubble in a liquid with the current parameters of the gas-liquid flow. Estimates of the relaxation times for the bubbly flow (small bubbles, gas evolution predominates) and slug flow (large bubbles, dissolution predominates), as functions of time from the beginning of the process, are obtained for the parameters of a real flow in a wellbore. It is shown that the obtained dependencies are consistent with the typical scaling of the diffusion process with respect to the size of bubbles. The results are important for mathematical simulation of gas-liquid flows in wellbores during hydrocarbon production, as well as for calculation of the gas-kick process during well drilling with oil-based muds.
Numerical simulations of gaseous flames in combustion chamber applications
Authors: Katona C , Safta C , Frunzulica F , Goemasn M 
Published: February 2021

Abstract
Recent developments and assessments of combustion models, numerical schemes and high-power computing allow simulations to be applied to real industrial thermal oxidizers and burners. In this paper, two type concepts in a complex geometry of a burner and combustion chamber is reviewed by means of measurements data from on-site during operations compared with the numerical simulation’s analysis. The combustion models as Flamelet, Flamelet Generated Manifolds (FGM) and Hybrid BML/Flamelet are performed to assess modeling and fundamental flow aspects of combustion instabilities in a swirl concept in the context of the Reynolds-averaged Navier Stokes (RANS) equations for gaseous flames. Simulations in real thermal oxidizers illustrate the prospective of the approach but the combustion modeling and chemistry sub-grid models are limited cases in terms of validations due to the lack of available advanced set of measurements. Specific issues associated to real thermal oxidizer are presented: on-site measurements during operations, multi-perforation of heat in the combustor walls and flame instabilities. The examples are assigned as mean flow predictions (velocity, temperature and species) and transient phenomena (ignition and flame instabilities). Finally, the conceptual differences of the potential perspectives are discussed in detail from a theoretical and practical point of view.
Optimizing thermo-mechanical processing and material coupling parameters in numerical modeling for additive manufacturing
Authors: Antoine Lamanna , Beauchesne Erwan , Pierre-Richard Dahoo , Meis Constantin 
Published: February 2021

Abstract
Additive manufacturing (AM) is gaining increasing industrial interest. Initially conceived to facilitate the pre-production, to manufacture efficiently and cheaply unique parts such as prototypes, it is now able to deliver parts that meet industrial production needs. In addition, AM is an effective way to achieve parts designed using topological optimization. Laser beam melting is an AM technique able to produce specific parts with mechanical properties matching industrial expectations. However, efficient production remains complex because of distortion, cracking and other failures linked to the process and to the machine parameters. The prime material being generally expensive and in order to achieve the required manufacturing quality from the very first attempt while reducing the processing time to market necessary for low cost mass production, a high-quality digital simulation is mandatory. We thus study the relation between the process and the material parameters with the final mechanical state of the part using a numerical model, which is developed in parallel.
This work focuses on the macroscopic scale. In order to carry out the thermo-mechanical study we use a finite element resolution method on the whole domain defined by the part, its supports and the baseplate. At this scale, one can neglect the packing of the powder as well as the hydrodynamic behavior of the melt pool in the laser beam melting process. We consider a Gaussian energy distribution for the heat source, imposed on several layers of powders below the deposited layer. Starting from a previous study [11], which considers the temperature dependence of the Young modulus, we improve, in this work, the model by considering the temperature dependency of other physical parameters pertaining to material properties or to elastoplastic and thermal laws coefficients. The aim is to bridge the macroscopic scale study of AM to the mesoscopic scale from results of this study.
In a first step, simulations are carried out with simple models like walls, cubes, beams and the popular cantilever used for calibrations. The results show the gain in precision with the contribution of the temperature dependence of various parameters as well as by considering the phase-transition during the printing process. The computing time is compatible with laptops and can iterate the simulations easily. The accuracy of the model is validated by comparing the distortion to the experimental results
Computation of the masses of neutrinos from the Hadron and Boson masses via the Rotating Lepton model of elementary particles
Authors: Vayenas C G , Tsousis D , Grigoriou D 
Published: February 2021

Abstract
We use the Rotating Lepton Model (RLM) of elementary particles in conjunction with special relativity and the de Broglie equation to compute analytically the masses of neutrinos from the masses of composite particles, such as hadrons, in the structures of which neutrinos have been recently shown to participate. In this way, three distinct neutrino masses are computed which are in good agreement with the values obtained experimentally at Superkamiokande for the three neutrino flavors of the Normal Hierarchy.
Inflation model with viscous fluid
Authors: Myrzakul S R , Tsyba P Yu , Razina O V , Myrzakulov Y M 
Published: February 2021

Abstract
We investigated f(R) gravity with k-essence using the Starobinsky model as an example, given by the expression f(R) = R + α
R
2. Using the hybrid function of the scale factor, we found the scalar field function and its potential. For the model under consideration, the parameters of the slow roll-off satisfy the inflationary stage. Our model allows us to obtain an accelerated expansion of the Universe during an inflationary period. A non-uniform non-viscous fluid was investigated, and then the viscosity was introduced in the second example. Received fluid equations for the accelerated universe.
On the stability of exponential variational integrators for multibody systems with holonomic constraints
Authors: Kosmas Odysseas 
Published: February 2021

AbstractIn the present we test the stability of the high order exponential variational integrators when applied to mechanical systems with holonomic constraints. Those geometric integrator schemes are determined by a discretization of a variational principle for a discrete Lagrangian. That expression, which is defined using exponential expressions of interpolation functions, is then applied on the discrete Euler-Lagrangian equations with constraints. The resulting schemes are then tested on a typical dynamical multibody system with constraints, i.e the double pendulum, and show good long-time behavior when compared to other traditional methods.
Convergence Analysis of Whale Optimization Algorithm
Authors: Feng Wentao 
Published: February 2021

Abstract
The whale optimization algorithm (WOA) has been widely used in different applications. It has simple control parameters and novel population updating mechanism. However, there is few theoretical analysis of WOA and the convergence property of WOA is ambiguity. This paper analyzes the convergence property of WOA by using the Markov chain of the stochastic process theory. The Markov chain model of the WOA algorithm is established. The one step transition probabilities and convergence properties of different population updating mechanisms in WOA are given. It’s proved that the convergence property of WOA is determined by its shrinking encircling mechanism. Finally, three algorithms with different population updating mechanisms are tested with thirteen benchmark functions on accuracy and convergence speed. The simulation results on benchmark functions verify the validity of the theoretical analysis of WOA.
Research on the Optimization of Staff Allocation under the Strategy of “Strong Leads the Weak”
Authors: Chen Chanjuan , Li Hanxu , Sun Junyan , Zhang Yuanyuan 
Published: February 2021

Abstract
Based on the operator’s competency index matrix, a two-layer mathematical model with the goal of maximizing the total competency of employees’ workstations is designed. The upper layer uses the Hungarian Algorithm to achieve the configuration of “strong employees”, and the lower layer uses the Hybrid Genetic Simulated Annealing Algorithm to achieve the configuration of “weak employees”. The results show that: compared with the traditional undifferentiated overall configuration. The double-level configuration based on the double-level mathematical model increases the employee competency difference ratio by 5.71%, which effectively embodies the idea of “strong leads the weak”.
Particle Swarm Optimization with Multiple Adaptive Subswarms
Authors: Jiang Xunlin , Yue Yingjie , Min Yinxing , Zhang Qingyu , Gui Xinxing 
Published: February 2021

Abstract
Benefiting from its simplicity and efficiency, particle swarm optimization (PSO) algorithm has shown great performance on various problems. However, for different optimization problems or different search areas, it is still difficult to achieve a satisfying trade-off between exploration and exploitation. On the basis of canonical PSO algorithm, a variety of improved algorithms have been proposed, which have different capabilities of exploitation and exploration, and each of them performs effective in some problems. This paper proposes a particle swarm optimization with multiple adaptive sub-swarms (PSOMAS). It uses multiple subswarms strategy, in which each sub-swarm is evolved by different algorithms, and an adaptive strategy is also used to reduce the consumption of computing resources. A comprehensive experimental study is conducted on 30 benchmark functions, to compare with several well-known variants of PSO algorithms. The results show that PSOMAS with RT=100 could obtain a better overall performance than all others. Moreover, PSOMAS could find high-quality solution in different problems by varying the value of RT.
Global Contrastive Person Re-identification
Authors: Pei Shengyu , Fan Xiaoping 
Published: February 2021

Abstract
Solving the problem of pedestrians being occluded by objects is extremely challenging. Using part-level features to describe pedestrian images can provide fine-grained information. However, only paying attention to the local features of body will lack global pedestrian information. And the network consumes time and memory. To solve these problems, we propose a new person re-identification network. The network uses a global contrastivemodule to obtain the features of pedestrians. Through effective use of the pedestrian’s global features, as well as the pedestrian’s personal information and global contrastive information, the pedestrian can be found in the object occlusion to provide a reliable feature embedding. Our model is tested on Market1501, Duke MTMC-reID, CUHK03 and MSMT17 datasets. The experimental results show that our method is effective in occluded person re-identification
Track Defect Detection Based on Neural Network
Authors: Nan Zhefeng , Xu Yan , Cao Wenrui 
Published: February 2021

Abstract
The maintenance and inspection of the high-speed railway is the core problem of railway safety. To solve the problems of insufficient network depth and low defect extraction ability, an improved Unet network model was proposed. in view of the relatively small defect area, the attention mechanism is used to effectively suppress the background and highlight the significant features of the defect. The experimental results show that the improved Unet model improves the comprehensive detection accuracy of defect targets by 6% compared with similar segmentation models.
TOR Anonymous Traffic Fingerprint Extraction and Recognition Based on Neural Network
Authors: Pu Tao , Wang Juan 
Published: February 2021

Abstract
The TOR anonymous communication system is an important means to protect network communication security and user privacy, but there are still criminals trying to destroy the confidentiality of the anonymous communication system through some special methods. Aiming at the abuse of the TOR anonymous communication system, this paper proposes a neural network-based anonymous traffic identification method, which uses a one-dimensional convolutional neural network for feature extraction, prediction and classification, and finally integration. In the experiment, nearly 100 websites were selected for the flow feature extraction and recognition based on one-dimensional convolutional neural network. The recognition accuracy rate is 87.5%, indicating that this method can effectively fingerprint TOR anonymous communication.
Intrusion Detection of Vehicle Based on Generative Adversarial Networks
Authors: Liu Ying Jiang , Wang Juan , Zhao Yang 
Published: February 2021

Abstract
In the process of applying deep learning to intrusion detection, in order to ensure the recognition accuracy of the model, a large number of data sets need to be classified manually, and then the model training is carried out after labeling. In practice, the efficiency of manual label designation for enough data sets is extremely low. This paper aims at the experimental data set encountered in the intrusion detection of intelligent network vehicles The problem of classification difficulty is proposed, and a method of vehicle intrusion detection based on Generative Adversarial Networks is proposed. Firstly, the vehicle driving data is collected, the collected data are put into the Generative Adversarial Networks for data classification, and the data set after training classification is used for model training. The experimental results show that the data classification can effectively improve work efficiency and reduce the resource overhead, which is practical in the application field.
Key Technologies and Applications In Intelligent Agriculture
Authors: Liu Qin , Yan Qing , Tian Jianying , Yuan Kexin 
Published: February 2021

Abstract
With the development of new generation information technology such as artificial intelligence, Internet of things and big data, traditional agriculture has changed and gradually changed to intelligent agriculture. In intelligent agriculture, sensor technology can collect all kinds of information in agricultural production, communication technology can transmit the collected information, and use big data analysis to guide agricultural production and agricultural product sales, The application of artificial intelligence makes agricultural production high-yield and high efficiency, and unmanned driving technology can realize automatic production and fine management. This paper elaborates the application of these key technologies in agriculture.
Research on New Media Content Production Based on Artificial Intelligence Technology
Authors: Wang Xiaocui , Liu Chuanlin , Qi Yue 
Published: February 2021

Abstract
At present, the main application of artificial intelligence in the media content production industry is to greatly reduce the application threshold, to a certain extent, to enable media workers to collect data from the low-end and produce visualization works for media terminals free from repetitive labor. Such as visual effects production, special effects design, video editing, subtitles sorting, data collection and comparison, image-text audio-video conversion, host broadcasting, and press release writing, are now increasingly completed through artificial intelligence programs. The working procedures of media content production are becoming more and more automated and intelligent.