bluuebunny/crossref_metadata_2025_split huggingface dataset:
Strengthening of polymer ropes based on polypropylene with carbon nanotubes
Authors: Zaporotskova I V , Elbakyan L S , Vilkeeva D E 
Published: August 2021

Abstract
The issues of using carbon nanotubes as fillers to strengthen polymer ropes used in the mining industry, oil and gas production, metallurgy, power engineering, etc. are considered in the work. The method for producing a nanocomposite based on polypropylene doped with carbon nanotubes has been developed. Experimental studies of the most significant strength characteristics of the created prototypes of polymer composite materials have been carried out. To determine the mechanisms acting upon the introduction of nanotubes into the polymer matrix, DFT calculations of the interaction of propylene monomer with the surface of single-walled nanotubes of different diameters and chirality have been performed.
Sensor activity of titanium dioxide nanotubes in relation to acetone molecules
Authors: Zaporotskova I V , Vilkeeva D E , Elbakyan L S 
Published: August 2021

Abstract
This paper presents the theoretical study results of the possibility of acetone, common volatile organic compound (VOCs) in human respiration, with titanium dioxide nanotubes. The efficiency of interaction of the acetone molecule with the TiO2 nanotube is analyzed. Recommendations for the creation of highly sensitive sensor devices using titanium dioxide nanotubes for diagnostics of various diseases have been developed.
Technological aspects of glass matrix production of temperature-resistant sitall coatings based on secondary industrial products
Authors: Lazareva E A , Minko N I , Yu Lazareva G 
Published: August 2021

Abstract
The paper considers technological aspects of the production of glass matrices of heat-resistant sitall coatings for the protection of nichrome alloys obtained on the basis of the RxOy-Al2O3-SiO2-TiO2 system (R = Li+, Na+, K+, Mg2+, Ca2+, Ba2+, Fe3+, Mn4) using secondary raw materials are considered. The results of experimental studies of the synthesis and physico-chemical properties of matrix glasses for slag-and-metal coatings are presented.
Modified early-strength concrete mix
Authors: Perfilov V A 
Published: August 2021

Abstract
This paper suggests new early-strength concrete mixes composed of Portland cement, coarse and fine aggregates, a complex modifying admixture containing carbon nano tubes and bishofite produced at the Volgograd deposit. The paper represents the findings of scientific and experimental research and describes the impact of the suggested admixtures on the structure formation, rheological, physical and mechanical properties of the early-strength concrete. The micro-structural analysis revealed that the concrete mix containing a complex modifier is characterized by compact cement-and-sand matrix and a more homogeneous structure at the interface with the grains of the coarse aggregate. Review of the test results proved that the suggested composition and the complex admixture dosage contribute to decreased water-cement ratio, increased fluidity of concrete and a higher strength of hardened concrete at the early and final hardening stages.
The degree of survivability of building structures under dynamic loading
Authors: Sarkisov D U , Galyautdinov D R , Zbojkova N A 
Published: August 2021

Abstract
The relevance of the work is due to the increasing possibility of impact on the critical building structures of industrial buildings of short-term dynamic loads in abnormal emergencies. These situations lead to significant damage of the constructions of buildings. There is a high possibility of human victims and significant damage of expensive technological equipment when the structures collapse. Therefore, in order to ensure further functioning of the structure, it is necessary to design building structures as well as the object on the whole with the properties of survivability under non-stationary impact. Such properties should be analyzed when constructing scenarios of origination and development of emergency situations as well as analyzing risks. In the course of the research the strain gauge methods were used to measure deflections, accelerations and loads on the samples. The work proposes a method for assessing the degree of survivability of a critical building structure under short-term dynamic loading based on the analysis of the energy parameter. Using the example of a specific test of a bending reinforced concrete element for short-term dynamic load the values of the specified coefficient were obtained.
Modeling of polarization relaxation of solid electrolyte LiPON in the low temperatures range
Authors: Novozhilova A V , Rudy A S , Tortseva Yu S 
Published: August 2021

Abstract
The paper presents the results of studying the polarization relaxation mechanism in solid electrolyte LiPON by the method of discharge through an external load. Test cells made in the form of encapsulated multilayer structures SiO2/Pt/LiPON/Pt/Ti/SiO2/Si were tested on a stand for discharge characteristics measuring. To explain the discharge curves, an equivalent LiPON circuit and a mathematical model of polarization relaxation during discharge are proposed. By fitting the parameters of a mathematical model, the Maxwellian relaxation times of lithium ions and that of the LiPON ionic polarization relaxation are determined.
Mathematical model of thermal processes in metals during pulse processing with concentrated energy fluxes
Authors: Kozyr’ I G , Komolikov A S , Kuzenkov S E 
Published: August 2021

Abstract
The paper considers mathematical modeling of thermal processes in metals during pulsed processing by concentrated energy flows. Calculations of thermal processes in steels under pulsed heating are given, considering the phase transformations and the temperature dependences of the thermophysical properties, as well as the space-time characteristics of the thermal energy source. It is shown that the created mathematical model is universal for various sources of thermal energy and adequately describes the space-time distribution of temperature fields during pulsed heating of the surface layers of metals and alloys.
The simulation of water-oil emulsion separation process in a settling tank with corrugated plates
Authors: Zinurov V E , Dmitriev A V , Patrakova G R 
Published: August 2021

Abstract
This research paper deals with the problem of increasing the efficiency of water-oil emulsion separation. In order to intensify the process of its stratification, the internal baffles with orientation of corrugations at an angle of 45° were studied. The numerical simulation of emulsion separation process inside the apparatus was conducted by means of ANSYS Fluent software package. In the course of studies, three models of apparatus of different geometrical dimensions were considered. Each subsequent design was by 50% larger than the previous one. The results of studies allowed to make a conclusion that the separation efficiency of water-oil emulsion is on average equal to 73.7%. At the same time, a peak range was determined, corresponding to the rates from 0.05 to 0.17 m/s, at which the separation efficiency is on average equal to 77.7%. The maximum separation efficiency of at least 80%, regardless of dimensions of apparatus, is achieved at the emulsion rate equal to 0.11 m/s and rates close to this value. The emulsion movement rate, the size and density of oil globules are the key indicators that affect the change in the efficiency of water-oil emulsion separation into components.
Model Construction for Far Field Eddy Current Examination Simulation on Ferromagnetic Tubes
Authors: Du Haoyang , Yang Zhou , Cui Lun , Xiao Huixu 
Published: August 2021

Abstract
Ferromagnetic tubes are widely applied in fossil power plants such as waterfall tubes, overheat tubes or reheating tubes. Outer surface corrosion, wearing, depth reduction, cracks are common defects during manufacturing and long term operation. Eddy current detection is a traditional method for the examination of surface and near surface defects. However the efficiency is restricted by lift-off effect and skim effect. Far field eddy current overcomes the above disadvantages with high efficiency and fast examination speed and high sensitivity. In this paper, numerical simulation has been carried out to study the far field eddy current Detection for defects in small diameter ferromagnetic tubes in fossil power plants.
3D Modeling for Kitchen Scene in a Hospital
Authors: Tsai Wen-Lung , Liu Xing-Ying 
Published: August 2021

Abstract
This research focused on hospital diet management to explore the design of 3D models for kitchen scenes and the facilities of a hospital. Hospital diet management has standard operating procedures, but most people have never seen the kitchen environment within a hospital. Hence, the ongoing research highlights the foodservice procedure and makes a live-action film to complete 3D modeling and animated scenes within a hospital. This research applied the 3ds Max and other multimedia technologies in the medical and healthcare fields. The presentation of the virtualized scene and facilities is realistic and detailed. This research illustrates that the diet management process can be done quickly by 3D modeling and animation. It can also be applied to healthcare education and train new employees who need to understand the carrier’s details as soon as possible.
Predicting the Cases of Hepatitis B with the A-LSTM Model
Authors: Li Yang , Yang Yali , Yang Cong , Zhang Baolin 
Published: August 2021

Abstract
Hepatitis B is a disease caused by hepatitis B virus. It’s of great value to predict the cases of hepatitis B because of its strong infectivity and carcinogenicity. To predict the monthly new patients of hepatitis B in China accurately, a neural network with an attention-based LSTM model is proposed. Driven by the historical data provided by the Data-center of China Public Health Science, the model’s evaluation indexes of RMSE, MAPE, MAE and R-squared are 1780.495, 1.789%, 1469.208 and 0.867 respectively, while the evaluation indexes of BPNN are 3532.959, 3.311%, 2677.009 and 0.478 respectively. The result shows that A-LSTM model in this work has an excellent prediction on the monthly new patients of hepatitis B and performs much better than BPNN and other traditional time series models.
Research on Data Extraction of Tibetan Dance Movements Based on Different Convolution Models
Authors: Zhang Lijun , Dong Jianmin , Ye Kai , Liu Jianxin 
Published: August 2021

Abstract
In order to strengthen the in-depth integration between culture and technology, and provide a certain theoretical basis for the improvement of the digital system of Tibetan dance and the innovation of Tibetan dance teaching, a new research method was proposed : based on high-definition Tibetan dance video data, we used OpenPose to extract the dancer's skeleton joint point data, and the five characteristics of Tibetan dance: "open", "tremor", "left", "round", "shun" and other characteristic movements were summarized. In the feature extraction stage, we tried different convolution methods to compare the extraction results. In the end, we extracted the dancer's bone point data more completely, deeply digitized the movement characteristics of Tibetan dance through digital technology. The experimental results show that the numerical feature rules of the five major characteristics are highly consistent with the dancer's performance analysis characteristics, which proves that the extraction and analysis method given is feasible.
Impulse Ground Pressure Prediction Based on Rough Set- Distance Discriminant Model
Authors: Ping Jian 
Published: August 2021

Abstract
In this paper, introduce the rough set theory, and the weight coefficient is calculated by analyzing the support degree and attribute importance of the evaluation object. Combine with the distance discriminant model, successfully construct the weighted distance discriminant model of rock burst, and determine the reasonable discriminant factors. Taking 15groups of data from Yantai Coal Mine as training samples, and establish the rough set distance discriminant model for rock burst prediction. The discriminant results of this model were compared with those obtained by Fisher analysis discriminant model (FDA), R-type factor Fisher discriminator method, etc. Through the comparison of the judgment results, prove the effectiveness of the through-distinction model in the field of mine water source discrimination. The results show that the through set distance discrimination model has the advantages of high prediction jurisdiction and strong rationality, and it is a new way suitable for mine water source discrimination.
Performance Analysis of FISSER Model in Rural-Urban Cognitive Radio Networks
Authors: Oki Olukayode , Olwal Thomas , Adigun Matthew 
Published: August 2021

Abstract
In the past few decades, Cognitive Radio network (CRN) has been regarded in the literature as the most promising technology for performing dynamic spectrum management. One of the major aspects of spectrum management is referred to as the spectrum-reconfiguration decision-making ability of CR users. Dynamic spectrum reconfiguration has previously been reported to improve the spectrum utilisation in CRN. In exploiting spectrum reconfiguration to improve spectrum utilisation, various approaches have been adopted to develop models. However, none of these research works has been evaluated in the urban and rural settlement context. In a CRN environment, the frequency availability is not static like that of traditional networks. There are resource-rich regions such as in rural areas, where many frequencies are available for the Secondary Users (SUs) and resource-poor regions such as urban areas, where there are only a few frequencies available for SUs. Hence, this paper proposed a novel Foraging Inspired Spectrum Selection and Reconfiguration (FISSER) model. The performance of the FISSER model has been analysed through computer simulations both in the rural and urban CRN, using high and low perceptual radii. A high perceptual radius has been shown in the literature to improve energy efficiency and data communication performance in ad hoc networks. However, the simulation results reported in this paper show that even though the high perceptual radius improves the nodes’ energy efficiency it does not achieve optimal data communication performance compared to when the nodes use a low perceptual radius. Also, the efficacy of FISSER model was tested by comparing it against the reinforcement learning model. Based on the obtained results, it was shown that the FISSER model achieved better results in both the network throughput and the channel switching time.
Sequential Emotion-Aware Recommendation: A Preliminary Study on Data Acquisition and Modeling
Authors: Chen Weihao , Zheng Lin , Jiang Dazhi 
Published: August 2021

Abstract
The rapid development of recommender systems makes researchers pay more and more attention to the utilization of users’ subjective factors. Among various subjective factors, emotion plays an important role that can truly reflect the temporal changes of users’ preferences. However, the acquisition of user emotion is difficult, and is obtained passively in many methods. Moreover, there are few datasets suitable for continuous emotion modeling in existing recommendation research. To address these shortcomings, this work collects and organizes a dataset of users watching movies containing their temporal emotional data, which is appropriate for recommendation tasks based on sequential emotions. In addition, we propose a sequential emotion-aware recommendation method suitable for continuous emotion modeling, which outperforms other advanced sequential modeling approaches on our dataset. The contribution of this work is to conduct preliminary study and exploration on the modeling of users’ sequential emotion, so that this research direction can be further developed in future. The Sequential EMotion-Aware Recommendation (SEMAR) dataset we collected is available at: https://github.com/LinZheng666/Sequential-Emotion-Dataset-for-Recommendation.
A Prediction Method Based on Extreme Gradient Boosting Tree Model and its Application
Authors: Lao Yongchang , Qi Fangzhong , Zhou Jiakai , Fang Xiaobao 
Published: August 2021

Abstract
Improving the accuracy of financing risk prediction is of great significance to the healthy development of grid enterprises. Taking a provincial-level power grid company as the research object, the financing risk index system is constructed by considering multiple dimensions, and the monthly financing risk index RI of power grid enterprises from 2015-2018 is determined based on entropy weight and comprehensive index method, while the financing risk prediction model is constructed with the help of extreme gradient boosting tree model. The empirical results show that compared with support vector regression and BP neural network models, the financing risk prediction model constructed based on the extreme gradient boosting model has an excellent performance in terms of prediction accuracy and stability.
Computational Efficiency of Three Programming Languages in N-body Simulation
Authors: Pan Junnan , Li Zhongmu 
Published: August 2021

AbstractThe computational efficiency of FORTRAN, C and Python languages in N-body simulation is investigated. The potential of these languages to promote the research of N-body simulation is therefore shown by this paper. Our work utilizes Particle-Particle (PP) algorithm, which not only balances the accuracy and efficiency, but also simplifies the traditional numerical calculation. The experimental results show that the computational efficiency of the three is almost the same in the case of a small number of particles, but FORTRAN shows the highest computational efficiency in the case of a large number of particles. The efficiency of Python is the lowest among three languages. The result suggests that FORTRAN is the best choice for N-body simulation, and Python should be used after optimizing the algorithm or working on extreme high-performance computers.
Simulation Analysis of Cam Wear in Shedding Mechanism of Loom
Authors: Dai Xin , Li Jing 
Published: August 2021

Abstract
Aiming at the serious wear of the cam surface in the shedding mechanism of the loom weaving, which is likely to cause uneven movement of the heald frame, this paper proposes to add a layer of copper-plated carbon fiber composite material to the cam surface to improve the cam wear during the operation of the shedding mechanism. In finite element ABAQUS®, the cam is modeled, material properties and boundary loads are set, and ALE adaptive mesh technology and Umeshmotion subroutine are also used for wear analysis. The simulation results show that under the same conditions, the wear between the cam and the roller with a copper-plated carbon fiber layer is much smaller than the wear between the pure metal cam and the roller.
Influence of Fluid Effect on Virtual Simulation of Otolith Movement
Authors: Kong Lingyi , Wu Jun , Feng Mingjie , Liu Zhaobang , Yang Xiaoguo 
Published: August 2021

Abstract
More and more physics engines are used to simulate the dynamics between two rigid bodies. However, it is still unknown whether physics engine is suitable for computing the physical information of objects with fluid effect, such as the trajectory and collision dynamics of otolith in semicircular canal in benign paroxysmal postural vertigo (BPPV). The purpose of this study is to determine whether the fluid effect in Bullet physics engine has an impact on the movement data of otoliths in semicircular canal. Based on the experimental data obtained previously, we discuss the position and trajectory of the otolith when it falls in the Dix-Hallpike test. Root Mean Square Error (RMSE) is used to evaluate the static position of otolith under two conditions, and the RMSE is 0.716. We found that the initial position of otolith is affected by fluid effects, but the final static position and trajectory of otolith is similar (x=-5.838±0.294, y=19.348±0.143, z=-9.540±0.635). The experimental results show that the fluid effect does not affect the experimental results of the Dix-Hallpike test, and it has sufficient applicability for the evaluation of BPPV diagnostic methods.
The Comfort Simulation of Double-wheel Intelligent Vehicles Considering Human Bodys
Authors: Gao Zhendong , Chen Xin , Hou Jing , Lin Zhangxi , Lv Shunya , Hong Bin 
Published: August 2021

Abstract
In this paper, aiming at the self-developed double-wheel intelligent vehicle, a comfort simulation considering the human two-DOF (degree-of-freedom) model was conducted. Based on the analysis of the human body response to the vibration, the dynamic model of vehicle random vibration is used to establish a five-DOF human-seating-road ride dynamic model combined with MATLAB/Simulink software. Through the simulation of the road comfort test under the excitation of filtered white noise, the ride comfort analysis of the intelligent vehicle was realized.
Research on Detection Method for Welding Seam Defects in Ultrasonic TOFD Image Based on Mask R-CNN
Authors: Wang Yimin , Cao Yongbei , Ye Birun , Zhang Huidi , Fu Yadi 
Published: August 2021

Abstract
In this paper, the technology of ultrasonic TOFD was used in the welding seam inspection of construction steel structure. 162 ultrasonic TOFD scanning images including five kinds of common defects were obtained through field test. The five kinds of common welding defects include stoma, slag inclusion, lack of fusion, incomplete penetration and crackle. Combined with artificial intelligence image recognition technology, an automatic detection algorithm of welding seam defects in ultrasonic TOFD scanning images based on Mask R-CNN was developed. By comparing the effects of automatic location and classification of welding seam defects based on Mask R-CNN after the same number of iterative training under different parameter configurations, the results show that Mask R-CNN can automatically locate and classify welding seam defects and the recognition effect is the best when epoch is 667, steps_per_epoch is 15 and learning rate is 0.001. Under this parameter configuration, the recognition and classification of five kinds of common defects such as stoma, slag inclusion, lack of fusion, incomplete penetration and crackle are correct. The correct recognition confidence of all five kinds of defects can reach more than 0.9, and the location is precise.
Application of Fuzzy Extension Analytic Hierarchy Process in Location Selection of Logistics Center
Authors: Yu He , Wang Nana , Pan Jiaqi 
Published: August 2021

Abstract
This paper use fuzzy extension analytic method to solve the problem of location selection of logistics center. First, establish an evaluation system. There are three first-level indicators at the criterion level, which are social benefits, economic benefits, and infrastructure, and nine second-level indicators at the sub-criteria level. The extension analytic method is used to compare all the factors corresponding to the layer to the first factor and use the number of extension intervals to compare them in pairs, so as to construct a judgment matrix for the extension interval and find the weight vector. Further hierarchical ranking is performed. Secondly, the fuzzy comprehensive evaluation method is used to determine the factor set and evaluation set of influencing factors, and the evaluation matrix is established. The primary element is used to determine the evaluation model. First-level evaluation is performed on each logistics center to obtain a second-level evaluation matrix. The model comprehensively evaluates the two-level evaluation matrix, and then ranks the evaluation levels of each which introduces extension theory, considers human ambiguity, uses interval numbers instead of specific numbers to construct a judgment matrix. The example proves that the ranking is more practical and provides a theoretical basis for site selection.