bluuebunny/crossref_metadata_2025_split huggingface dataset:
Formation mechanism of Ni-Cu-base coatings with diffusion alloying into low-melting liquid metal media solutions
Authors: Sokolov A G , Bobylyov E E , Storogenko I D 
Published: August 2021

Abstract
The paper shows the mechanism and kinetics of the formation of diffusion coatings deposited in the medium of low-melting liquid metal melts depend on the nature of the interaction of the elements forming the coatings with the elements of the coated steel. When applying a coating based on Ni-Cu, the following features were revealed: the presence of a process of carbon displacement by the coating elements deep into the coated material; the practical absence of the influence of the carbon concentration in steel on the coating formation process; the elements of the coated material that do not interact with the coating elements are pushed deep into the product. The paper presents a scheme for the formation of diffusion coatings. Formulas for calculating the diffusion fluxes and the coating thickness are presented.
Surface morphology of nanostructured zinc oxide materials obtained by plasma-enhanced chemical vapor deposition
Authors: Mochalov L A , Logunov A A , Prokhorov I O 
Published: August 2021

Abstract
Zinc oxide nanostructures have been obtained by plasma-enhanced chemical vapor deposition technique. High-purity elemental zinc was used as the precursor. RF (40MHz) inductively coupled plasma discharge was used for the initiation of the plasma-chemical reactions in the gas phase. Hydrogen-oxygen (H2-O2) composition of various ratios was used as the source plasma gas mixture. The optical emission spectroscopy was used as the powerful tool to determine the intermediate excited particles and assume the possible mechanism of the plasma-chemical reactions. The paper also investigates the influence of the substrate’s materials, its temperature, and the power of the heat input into the discharge. The properties of the sprayed materials were characterized by the method of atomic force microscopy.
Magnesia compositions with technogenic fillers
Authors: Miryuk O A 
Published: August 2021

Abstract
The paper presents the results of researching magnesia compositions, which contain caustic magnesite and porous technogenic fillers. The research is aimed at creating resource-saving magnesia materials with the density less than 1000 kg/m3. The dependence of the magnesia composition’s density and strength on the size of arboreal particles is exposed. The increase of the particles’ size lowers the density of materials, but worsens the moulding characteristics. The influence of ash microsphere on the structural and mechanical properties of magnesia materials is found out. The content of hollow particles in the magnesia mixture is restricted due to the decrease of the raw materials’ mass plasticity. The mathematical models, presenting the dependences of moulding mass’ properties and composition density on the filler’s composition, are obtained. The compositions of raw materials’ mixtures for getting materials with a reduced density are determined. Moulding masses, which contain the integral filler (20-50% of arboreal particles with the size 0.63-2.5 mm and 50-80% of the ash microsphere), are preferable. The combination of fibrous and spherical hollow particles provides mouldability of the raw materials’ mixture as well as a reduced density of magnesia compositions. The electronic microscopy is used to research the materials’ structure.
Deformation of the prefabricated monolithic cover from porous concrete reinforced with fiberglass fittings
Authors: Miryuk O A , Oleynik A I , Akhmedov K M 
Published: August 2021

Abstract
The paper studies the properties and the possibilities of using definite size thin-walled fasciae from the lightweight concrete, reinforced with one-layer fiberglass fittings, by numerical methods. The object of the research is a standard element of the prefabricated monolithic reticular cover’s clothing under the plane stress. Plane prefabricated cells have a hexagonal shape and ribbing that make a basis for a common reticular framework after the assembly of the cover. Strength properties of the model are studied at different reinforcement degrees. The paper also researches the possibilities of increasing the fittings’ adhesion ability due to the regular curved structure. The comparison of different reinforcement variants is presented. The distributive function of the contour ribbing on the stressed state of the standard element is evaluated. The paper also gives recommendations on the use of discrete thin-walled reinforced elements as the elements of the bearings’ covers in the structure of multilayer or multilayer membranate constructions.
Computer simulation of crystals formed from 4-6-12 and 5-7 fluorographene layers
Authors: Belenkov M E , Chernov V M 
Published: August 2021

Abstract
The three-dimensional structure of four fluorographene crystals was calculated by the atom-atom potential method. The crystals consisted of 4-6-12 or 5-7 graphene layers functionalized by fluorine packed in stacks. The structure of fluorographene layers of two polymorphs T1 and T3 for 4-6-12 layer and two polymorphs of 5-7 layer T1 and T2 was considered. The electronic structure was calculated by the density functional theory method in the generalized gradient approximation. As a result of the calculations, it was established that the interlayer distances in various fluorographene crystals vary in the range from 5.4921 to 5.7645 Å. In CF-L4-6-12 T1 crystals, the relative shift of adjacent layers is close to zero. In the remaining fluorographene crystals, the layer shift vector varies from 0.336 to 0.3714 nm. The energy of interlayer bonds per atom is minimal for CF-L5-7 crystal of T2 type and is -3024.44 J/mol. The maximum value of the binding energy is equal to -2291.35 J/mol and observed in CF-L4-6-12 crystals of T3 type. The sublimation energy varies from 13.83 to 14.24 eV, and the band gap from 2.827 to 3.682 eV. The band gap in CF crystals is 0.2--0.4 eV less than in isolated fluorographene layers.
The theoretical evaluation of new promising solid ion conductors for zinc-ion batteries
Authors: Morkhova Ye A , Kabanov A A , Leisegang T 
Published: August 2021

Abstract
Recently, we have screened the Inorganic Crystal Structure Database (ICSD, version 2020/1) to find new Zn2+-ion conductors. After a stepwise selection procedure, we have identified five most promising Zn-ion conductors ZnFe2O4, ZnV2O4, ZnCr2O4, ZnP2O6 and Zn3S2O9. In this work we describe the ion conductivity in the selected structures in detail by using of a set of methods: analysis of free space in crystals (geometrical-topological analysis, based on the Voronoi partitioning approach), calculation of the Zn2+-ion migration energy barrier within the bond valence site energy method, and calculation of the Zn2+-ion energy barriers within the density functional theory approach.
Modelling and Simulation Analysis of Drones Allocation for Bushfires
Authors: Wang Junxu , Weng Haisong , Yan Yuxin , Li Congduan 
Published: August 2021

Abstract
Recent years, bushfire has been more and more frequent because of climate changes. At the scene of fires, firefighters have used drones for surveillance. In this paper, a model is designed to determine the optimal number of drones needed for a bushfire based on the data from satellites. We design a greedy algorithm to plan the cruise lines with the minimal number of drones, covering the fire region. We divide a region (take Victoria, Australia as an example) into blocks, and analysed each block to get the average number of drones needed. We also model the fire probability distribution and finally determine the total number of drones that should be reserved. The simulation (The simulation code is publicly available via https://github.com/WRangers/msadab) results and analysis show the model is effective and can adapt to a real-time changing large-scale bushfire situation, adjusting the cruise scheme dynamically. The algorithm is helpful to make a budget on purchasing equipment, and also helps the fire department deploy drones in bushfires.
Simulation Study on Tensile Strength of Carbon Fiber Twisted Sewing Thread
Authors: Zhang Yinfei , Li Jing , Cao Lingling , Peng Zhen , Han Wendong 
Published: August 2021

Abstract
The twist of the suture is an important parameter that affects the suture effect. If the suture is not twisted, the suture is easy to wear and fluff during the sewing process, resulting in thread breakage. At the same time, that will affect the suture effect and the strength of the suture itself. The article uses experiments and simulations to compare the mechanical properties of carbon fiber twisted threads. Refer to GB/T 3362—"Test Method for Tensile Properties of Carbon Fiber Multifilament" to test the tensile strength of T700-12K carbon fiber tow. And in ABAQUS, the three-dimensional Hashin damage criterion is used for 20 twists/m, 50 The carbon fiber sewing thread with twists/m and 80 twists/m is subjected to finite element prediction. The results show that the carbon fiber sewing thread with 80 twists/m has higher tensile strength than the carbon fiber sewing thread with 20 twists/m and 50 twists/m.
Simulation on the Effect of Frequency and Ferromagnetic Tubes Specifications by Far Field Eddy Current Examination
Authors: Du Haoyang , Cui Lun , Yang Zhou , Zhu Daming 
Published: August 2021

Abstract
Tube leakage frequently occurred in on-service fossil power plants. Traditional NDT testing methods, including RT, UT, MT and PT are not applicable for the examination of large amount tubes. Fat eddy current examination is a new technique for testing ferromagnetic tubes defects, such as inner corrosion, thickness reduction and cracks. Far field eddy current simulation and verification for different specification tubes has been carried out. The result shows that the position of far field eddy current moves backwards with the increase of wall thickness and tube ID. To the defects with same size, examination sensitivity is higher in far field eddy current area. When the defect with same size locates in the inner and outer surface of the tube, the change of magnetic intensify differences is approximately the same, which is in accordance with the experimental result and is satisfied with far field eddy current examination theory. It has been concluded that defects in ferromagnetic tubes could be judged and recognized by far field eddy current examination technique, which shows prospective for the on-line examination and safety evaluation for in-service tubes in fossil power plants.
Rough Set-Fisher Discriminant Analysis Method for Prediction of Classification of Rock Burst Risk
Authors: Ping Jian 
Published: August 2021

Abstract
This paper introduces the rough set theory, combined with the Fisher discriminant method to more accurately predict the risk level of rock burst. Firstly, based on the example of Yanshitai coal mine in Chongqing, we determine the influencing factors of rock burst risk; then, the evaluation indicators are reduced by rough set theory to obtain the key attributes; finally, the reduced key attributes are used as the discriminant factors of the rough set-Fisher discriminant model to test. According to the research results, the rough set-Fisher discriminant analysis method eliminates redundant indicators and reduces the number of indicators after reducing the evaluation indicators, achieving efficient prediction of the risk level of rock burst.
Mechanical Properties Test and Simulation Analysis of Glass Coated Amorphous Filaments
Authors: Qin Shujuan , Yin Junqing , Liu Shan , Chen Yongdang , Gu Jinyu 
Published: August 2021

Abstract
Taking the Co68.7Fe4Ni1B13Si11Mo2.3 glass-coated amorphous microwire as the research object, the mechanical properties of the amorphous wire were tested through biaxial tensile experiments, and the fracture deformation process of the amorphous wire was analyzed. Based on the experimental data, the finite element method was used The simulation software ABAQUS numerically simulates the tensile deformation of the amorphous wire, and the fracture relationship between the glass cladding layer and the core wire, and further reveals the tensile deformation fracture behavior of the amorphous wire was analyzed. The experimental results indicate that the fabricated microwires exhibit good tensile properties, and the maximum tensile breaking strength can reach 2918MPa; the fracture of the amorphous wire is a typical brittle fracture, and there is no obvious yield phenomenon. The tensile mechanics simulation results of the amorphous wire are consistent with the experimental results. The glass cladding layer breaks before the core wire, and the stress transfer effect in the amorphous wire is good. The model fracture is consistent with the fracture morphology of the amorphous wire. These results show that the amorphous wire exhibits good tensile properties and stress transmission capabilities, confirming the huge application potential of amorphous wire materials in sensor applications and functional composite materials.
Spatial Optimization Information Security Algorithm for UAV Cluster Oriented to RSA
Authors: Luo Guilan , Zhu Yuanbo , Wang Shuailin , Li Zhongmu , Zhang Mei , Wang Xi 
Published: August 2021

Abstract
In the face of the limited communication and computing capacity of UAV network in complex environment, in order to improve the operating efficiency of UAV cluster information security algorithm, this paper proposes a spatial optimization information security algorithm for Public Key Cryptography (RSA). Firstly, the UAV location and cluster space optimization algorithm (CA-PSO) is used to obtain the UAV location. Secondly, the optimal particle of UAV swarm is found through spatial optimization. Then the optimal particle is loaded with the UAV Cluster Information Security Optimization Algorithm (RSA-UAV). Finally, the UAV network simulation process is given. Through algorithm simulation and performance analysis, it is found that the positioning accuracy and convergence of the loaded information security algorithm are better after the improved algorithm space optimization.
Single Image Super-resolution Reconstruction Algorithm Based on Deep Learning
Authors: Li Qinqin , Guo Xiaoming , Han Jiangxue , Zhang Xiaoyang , Liu Heng 
Published: August 2021

Abstract
Recover the high-resolution image from a single low-resolution image is known as single image super-resolution reconstruction (SISR). SSIR is currently a research hotspot in computer vision. In this paper, we study the feature learning module of the magnification-arbitrary network for Super-Resolution(Meta-SR), and propose an improved method of image feature learning. Its idea is multi-scale residual dense block (MRDB). We integrate it into the existing structure of the Meta-SR network. As a result, the same network has increased the receptive field, and it can obtain more detailed features of the image. This structure can be extended to other existing SISR network models. In the published and standard test set Set14, compared with the interpolation method, the average PSNR value of the algorithm in this paper increases by 3.79dB, 3.01dB and 2.85dB at amplification factors 2, 3 and 4, respectively. Through the analysis of SISR results, it can be obtained that the improved method proposed in this paper has a significant improvement in all indicators, and can more fully extract the image detail features, thereby improving the quality of the reconstructed image.
Optimization of Helicopter Rotor Airfoil Wind Tunnel Test Model Based on Intelligent Algorithm
Authors: Kong Peng , Peng Xiaoqiang , Zhang Weiguo , Lian Zhenzeng 
Published: August 2021

Abstract
The helicopter rotor wing wind tunnel test model is the basic equipment for helicopter wind tunnel test research. On the premise of meeting the requirements of corresponding strength, stiffness, natural frequency and stability, the model mass needs to be light enough to meet the requirements of heave vibration test. To this end, this paper proposes the structure of aluminum alloy skeleton + carbon fiber reinforced composite skin, and in order to obtain good performance, the following steps are used to optimize the parameters of the test model structure: 1. Establish an RBF neural network approximation model; 2. Use multiple island genetic algorithm (MIGA) and the sequential quadratic programming algorithm (SQP) are combined to optimize the thickness of the skeleton and composite materials. The optimization results show that the quality of the model is reduced by 34.05% under the condition that the corresponding requirements of strength, stiffness, natural frequency and stability are met.
A Data Compress Algorithm for Daisy Chain Communication System
Authors: Xu Ziyang , Wang Yu , Gong Ci , Chen Junkang , Zhou Jian , Lu Yi , Zhang Xinyu , He Longyu , Huang Zihao 
Published: August 2021

Abstract
In the era of big data, traditional data compression methods cannot complete data compression with features of large volume, rapid growth and complex structure, especially in the processing of real-time data compression. The compression algorithm proposed in this paper is improved on the basis of a lossless bit-swap compression coding algorithm. The coding algorithm is based on VAE model and uses classical ANS compression technology to code multiple potential variables, so as to realize the rapid compression and decompression of data. The experimental results show that the algorithm proposed in this paper can compress data with a high compression rate(47.65%), which is higher than LZAM algorithm and Bit-Swap algorithm.
Implicit Aspect Extraction from Online Clothing Reviews with Fine-tuning BERT Algorithm
Authors: Yu Li , Bai Xuefei 
Published: August 2021

Abstract
In the era of e-commerce, tremendous product reviews can provide quick and valuable insight into the market trends. Aspect-based sentiment analysis (ABSA) on product reviews is becoming increasingly important for both companies and consumers. Implicit aspect extraction, a subtask of ABSA, aims to identify the aspect of a review sentence without explicit aspect terms. For Chinese online reviews, this paper proposes a fine-tuning BERT based method to extract implicit aspects. Fine-tuning BERT performs well on a variety of natural language processing tasks. Using labeled data, the hidden layer parameters of pre-training BERT are fine-tuned in a supervised manner to generate fine-tuning BERT. Through experiments on Chinese online reviews of clothing, it is believed that fine-tuning BERT can improve the effect of implicit aspects identification.
Algorithm Research on Manufacturing Agglomeration under the Background of Regional Integration Based on GMM Model
Authors: Lu Qiyuan 
Published: August 2021

Abstract
With the development of the process of regional integration, the manufacturing industry is also changing. This has attracted more attention. However, in the background of regional integration, there are relatively few empirical studies investigating the degree of manufacturing agglomeration. This paper selects nine cities in the Pearl River Delta, Guangdong Province, China from 2007 to 2017 as our sample. We use the Difference GMM Model to explore the impact of government support and labor concentration on manufacturing agglomeration. The measurement results show that both government support and labor concentration have a positive correlation with the degree of manufacturing agglomeration. Government support and labor concentration have different significance levels and coefficients for manufacturing agglomeration. In order to promote the increase in the agglomeration of the urban manufacturing industry, the increase in labor concentration will be more effective than government support.
Research on Object Detection Algorithm Based on Deep Learning
Authors: Li Meian , Zhu Haojie , Chen Hao , Xue Lixia , Gao Tian 
Published: August 2021

Abstract
The current target detection models have the characteristics of large storage, large demand for computing resources and large number of parameters, which are difficult to be implemented on the platform with low computing performance and small storage capacity. In order to reduce the size of the model and improve the detection speed, this paper proposes a new network architecture of mobilenetv2-yolov5s by combining the lightweight network mobilenetv2 with yolov5s Compared with other target detection algorithms, the improved yolov5s has better detection effect. The mobilenetv2-yolov5s network is tested on MS coco data set, and the mAP value is 55.1. While ensuring the map, the detection speed of the algorithm is 31fps, which is 25fps higher than yolov5s.
A Compilation Options with Optimization Techniques for IoT Network Systems
Authors: Cho Doosan 
Published: August 2021

Abstract
A compiler provides a variety of optimization options for execution speed, program size and energy consumption. Optimization options are provided by an optimizing compiler that supports hundreds of optimization techniques. In IoT network devices, it is difficult to apply an appropriate optimization technique required in specifications, because there are too many compilation options without detailed information about these options. In this study, we study various optimization techniques that can be applied by the compiler, and examine whether there is a side effect between the optimization techniques. Because optimization techniques are a series of tasks that change program code, side effect can be exist between the optimization techniques. As a result, certain optimization techniques can yield damage to the result of other techniques. To the best of our knowledge, there are few research on the side effect between various optimization techniques for IoT network devices, this study provides information that helps scheduling the optimization techniques.
Blade Profile Design and Optimization of Ocean Energy Low-speed Water Turbine
Authors: Lan Fuchuan , Liu Jiani , Zhang Fuxi , Wang Shiming , Chi Rong 
Published: August 2021

Abstract
Based on multi-objective genetic algorithm, naca4415 airfoil (NACA airfoil is a series of airfoils developed by the National Aeronautical Advisory Committee of the United States) is used as the original airfoil to optimize the blade airfoil of low water speed tidal current turbine, The lift drag ratio of the generator airfoil is improved (lift drag parameter is one of the key factors to determine the low-speed water kinetic energy conversion efficiency of the airfoil), the power generation efficiency of the turbine airfoil is improved, and the s airfoil is spliced on the basis of the optimized airfoil. The results show that the lift drag ratio performance of the optimized airfoil at the designed angle of attack is improved compared with that of the unoptimized airfoil, and the lifting range increases with the increase of the angle of attack. The pressure coefficient of the optimized airfoil decreases and the flow velocity increases. The pressure coefficient of the assembled S-shaped airfoil and the S-shaped airfoil have good bi-directional energy harvesting performance at the optimal attack angle of 12° to 15 °