bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of Parallel Algorithm Technology for Time Series Data Mining
Authors: Wang Wei , Hu Xiaohui , Wang Mingye , Du Yao 
Published: November 2021

Abstract
With the rapid development of computer technology, Internet technology and artificial intelligence technology, the amount of global data has exploded. However, the single-machine serial mode of traditional data mining cannot be directly transplanted to the cloud platform. Only by parallelizing and improving many classic data mining algorithms can the cloud computing platform and data mining be effectively combined. Therefore, it is of great significance to the research and implementation of parallel algorithm technology for time series data mining. The purpose of this paper is to study the research and implementation of parallel algorithm technology for time series data mining. This paper adopts the method of literature data, mathematical statistics, logic analysis and other research methods to study the parallel algorithm technology research and realization of time series data mining, mainly to make useful explorations of time series data mining and visualization technology. It embodies the design ideas of big data analysis tools, and finally reflects the power and market value of data analysis tools through the display of the platform. Research shows that running in the same data set and the same experimental environment, the improved parallel collaborative filtering algorithm ACF in this paper has higher time running efficiency than the parallel algorithm MCF based on the cooccurrence matrix, and in the case of larger data sets, the more obvious the time difference.
RETRACTED: Power Intelligent Customer Service Robot Based on Artificial Intelligence
Authors: Chen Lin 
Published: November 2021

Abstract
With the rapid development of speech recognition technology, voice chat robot has become a breakthrough of artificial intelligence. Voice chat robot should be a typical application field of customer service, providing customers with efficient and convenient service all day. The traditional customer service center is mainly based on telephone service, facing the problems of large number of customers, high maintenance cost, slow knowledge update, limited service time, low training cost and so on. So, at the same time, the use habits of customers have also changed fundamentally. The vast majority of services and transactions can be carried out through the Internet, such as Taobao and Jingdong. However, the quality and cost of voice services can be greatly reduced through the interaction between robots and channelization voice service centers. Through the research and development of natural language technology, an intelligent and centralized mobile communication service application platform is constructed by using we-chat platform. Through natural language processing, machine learning, big data computing and other technological innovation, we focus on the use of online robot recognition to understand customer problems and timely feedback customer needs. The results show that in the statistics of customer service machine problems, the highest proportion of consumers’ problems about payment is 37%, and the lowest is 29%.
Scene Understanding Technology of Intelligent Customer Service Robot Based on Deep Learning
Authors: Zhong Jianfeng 
Published: November 2021

Abstract
As a value-added service that improves the efficiency of online customer service, customer service robots have been well received by sellers in recent years. Because the robot strives to free the customer service staff from the heavy consulting services in the past, thereby reducing the seller’s operating costs and improving the quality of online services. The purpose of this article is to study the intelligent customer service robot scene understanding technology based on deep learning. It mainly introduces some commonly used models and training methods of deep learning and the application fields of deep learning. Analyzed the problems of the traditional Encoder-Decoder framework, and introduced the chat model designed in this paper based on these problems, that is, the intelligent chat robot model (T-DLLModel) obtained by combining the neural network topic model and the deep learning language model. Conduct an independent question understanding experiment based on question retelling and a question understanding experiment combined with contextual information on the dialogue between online shopping customer service and customers. The experimental results show that when the similarity threshold is 0.4, the method achieves better results, and an F value of 0.5 is achieved. The semantic similarity calculation method proposed in this paper is better than the traditional method based on keywords and semantic information, especially when the similarity threshold increases, the recall rate of this paper is significantly better than the traditional method. The method in this article has a slightly better answer sorting effect on the real customer service dialogue data than the method based on LDA.
VR Reality of the Relationship between Augmented Reality and Virtual Reality in the Context of Virtual Reality
Authors: Pan Yongming 
Published: November 2021

Abstract
With the development of virtual reality technology and its application in various fields, how to realize the natural and efficient interaction between human and virtual environment has always been a hot research issue. This paper mainly studies the realistic analysis of the relationship between augmented reality and virtual reality under the background of VR virtual reality. Starting from the research on virtual reality, this paper combines the features of virtual reality with the elements of visual presentation to conduct research on visual presentation in the sensory experience of virtual reality, analyze and find out the types and quantitative methods of visual presentation. This paper is supported by advance research, which is more in line with people’s perceptual needs for visual presentation. This study expands the research content of virtual reality visual presentation, provides guidance for virtual reality design practitioners, and has certain value and practical application prospects.
Optimal Scheduling Strategy for Real-time Charging of Electric Vehicles Based on Deep Learning
Authors: Gao Shixiang 
Published: November 2021

AbstractIn recent years, the automotive industry has informed the development situation. Under the problems related to automobile exhaust emissions and serious air pollution and energy shortages, new electric vehicles have sufficient advantages due to their low emissions, high energy efficiency, and low noise. It has been recognized by the people and governments of all countries. The research purpose of this paper is to meet the electricity demand of users, adopt the boundary model of charging and discharging energy and fully adopt deep learning to optimize the real-time charging optimization scheduling strategy of electric vehicles. In order to meet the electricity demand of users, the charge-discharge energy boundary model is used to characterize the charge-discharge behavior of electric vehicles. After the day-ahead training and parameter saving of the proposed model, according to the real-time state of system operation at each moment of the day, the charge-discharge scheduling strategy at that moment is generated. It is verified that the proposed charging scheduling method based on deep reinforcement learning can effectively reduce the power fluctuations in the microgrid and reduce the daily charge and discharge costs on the premise of meeting the charging needs of users; during the development of electric vehicles, different electronic components, especially the power consumption of electric motors, must be faced. A deep learning algorithm based on an improved recurrent neural network (MRNN) is proposed. The system is modeled according to different data and parameters inside the vehicle, and the network is modeled by the MRNN deep learning algorithm. Carry on training, predict the power demand and provide the best power, so as to expand the mileage, better optimize the power distribution of the motor, and compare the improved models. Experimental research results show that the efficiency of the related scheduling strategy model is increased by about 37.2% compared with the traditional model. The proposed method is fast in calculation and does not require iterative calculation, which fully meets the needs of real-time scheduling.
Discussion on the Innovation and Transformation of IMM and Processing Mode
Authors: He Miao 
Published: November 2021

AbstractThe progress of manufacturing is the driving force and foundation of social development, and the manufacturing industry represents the country’s production level and comprehensive strength. With the continuous development and advancement of science and technology, intelligent manufacturing has transformed the traditional labor-intensive manufacturing model, which can optimize the production management process of the enterprise to a large extent and reduce the manufacturing cost. This article aims to explore the innovative transformation of intelligent machinery manufacturing (IMM) and processing models. This article first analyzes the current situation of my country’s manufacturing industry to promote intelligent manufacturing, and points out the problems that exist in the development process. Based on existing problems, this paper takes manufacturing company H as an example, through questionnaire surveys and actual research methods, explores the advantages of H company in the development of intelligent manufacturing, and finally puts forward the promotion of intelligent manufacturing capabilities and intelligent processing in the manufacturing industry. The survey data shows that among 212 people, 140 people think that H company has a clear intelligent manufacturing plan, 152 people think that the company’s human-machine cooperation is efficient, and 157 people think that the company’s production equipment technology is perfect. This shows that the advantages of H Company’s production process are: clear goals in the intelligent manufacturing transformation plan, better business cooperation between various departments, perfect management of standardized operations in the workshop, higher coverage of automation equipment, and better human-machine coordination capabilities.
Investigation of the gap bridgeability at high-power laser hybrid welding of plasma-cut thick mild steels with AC magnetic support
Authors: Üstündag Ömer , Bakir Nasim , Gumenyuk Andrey , Rethmeier Michael 
Published: November 2021

Abstract
One of the challenges of the high-power hybrid laser welding of thick steels is the sensitivity of the process of the process to manufacturing tolerances. This usually leads to a time-consuming preparation of the welding edges, such as milling. The study deals with the influence of the edge quality of milled and plasma-cut steel made of S355J2 with a wall thickness of 20 mm on the laser hybrid welded seam quality. Furthermore, the gap bridgeability and the tolerances towards edge misalignment was investigated. An AC magnet was used as backing support to prevent sagging and positioned under the workpiece, to generate an upwards directed electromagnetic pressure. The profiles of the edges and the gap on the top and root side were measured using a digital camera. Single-pass laser hybrid welds of plasma-cut edges could be welded using a laser beam power of just 13.7 kW. A gap bridgeability up to 2 mm and misalignment of edges up to 2 mm could be achieved successful. Additionally, the independence of the cutting side and the welding side was shown, so that samples were welded to the opposite side to their cutting. For evaluation of internal defects or irregularities, X-ray images were carried out. Charpy impact strength tests were performed to determine the toughness of the welds.
Influence of laser-induced plasma parameters on the formation of laser-induced surface-periodic structures
Authors: Kochuev D A , Voznesenskaya A A , Galkin A F , Khorkov K S , Chernikov A S , Chkalov R V 
Published: November 2021

Abstract
The paper presents the results of processing a silicon surface with subpicosecond laser pulses under various exposure conditions. The variable conditions were: pressure in the working chamber, the speed of scanning the silicon surface with a laser beam and the laser pulse energy. Special attention was paid to the interaction of the laser-induced plasma plume with the surface of the processed material, with laser radiation and with the medium. The influence of the medium on the parameters of the laser-induced plasma is estimated. The result of this interaction is a change in the spatial characteristics of the laser-induced plasma channel, the period and type of the formed periodic surface structures, what is related to the change in the laser radiation passing through the medium at different pressures.
Effect of thermal cycles on the microstructure and mechanical properties of cold-resistant steel 09CrNi2MoCu during laser deposition
Authors: Mendagaliyev R , Klimova-Korsmik O G , Ivanov S Y , Babkin K D , Vildanov A M 
Published: November 2021

Abstract
The formation of microstructure features of cold-resistant bainite-martensite steel 09CrNi2MoCu has been investigated. Thermal cycles during direct laser deposition were studied. The thermal cycles at different points of the deposited samples were investigated. The thermal cycles and CCT diagrams on microstructure formation and mechanical properties have been analyzed. The numerical calculation of the three-dimensional thermal conductivity problem by the finite element method is carried out. The received data of experimentally measured thermal cycles and the calculated data have shown good coincidence of temperature values. On the basis of the obtained data the calculated dependence of inter-layer temperature at depositing the sample with and without a pause is given. The microstructure and mechanical properties of the samples in the initial state and after heat treatment have been studied and compared with traditional hot rolling. The microstructure features at different pauses between passes in different parts of the obtained samples were revealed. The effect on static tensile and impact toughness at -40°C in the bred and heat-treated state was investigated.
Characterization of Ni-Cr-Mo alloy phase structures under DLD process
Authors: Rashkovets R M , Nikulina A A , Klimova-Korsmik O G , Smirnov A I , Veselov S V , Kislov N G 
Published: November 2021

Abstract
Direct laser deposition of Ni-Cr-Mo alloy has been carried out to study the phase structure transformation under various operating parameters. To assess the phase composition SEM, TEM and XRD analysis were performed. It clearly seen that the precipitation of straightening phases (γ' and γ") depends on the temperature gradients caused by different laser power. The nucleation of γ' phase starts at 750 W while γ" phase at 1000 W. The changes in temperature gradients lead to different diffusion condition across all the stage of laser power variation and formation of δ-phase, primary MC carbides and Laves phase. δ-phase of all samples did not change the shape and characterized only by plate-like shape.
Structure and properties of near-a titanium products obtained by direct laser deposition and heat treatment
Authors: Shalnova S A , Klimova-Korsmik O G , Arkhipov A V , Yunusov F A 
Published: November 2021

Abstract
Advanced techniques of obtaining products require careful selection of materials for various industries. Titanium alloys are widely used in the aerospace, shipbuilding and mechanical engineering industries. The development of near-a titanium alloys should be considered a significant achievement in the field of metallurgy and heat treatment (HT) of titanium alloys. This article presents a study carried out with the aim of optimizing heat treatment modes for high-temperature titanium alloys obtained by direct laser deposition (DLD). Heat treatment was carried out in the temperature range (700-1000°C), covering three typical temperature ranges, i.e. the temperature range for the partial decomposition of martensite, the temperature range for the complete decomposition of martensite, and the phase transformation temperature were subsequently selected as the heat treatment temperatures. Based on metallographic analysis, the influence of heat treatment modes on the structure, as well as the tensile properties at room temperature, of TA15 titanium DLD-samples.
Investigation of the characteristics of ion saturation current in plasma over the keyhole in the process of electron beam welding
Authors: Sliva A P , Kharitonov I A , Goncharov A L , Dragunov V K , Gudenko A V , Terentyev E V 
Published: November 2021

Abstract
The energy spectra of the ion saturation current of the Langmuir probe in the plasma formed over the keyhole directly during the process of electron-beam welding of steel 09G2S with the varied parameters (e.g., the welding speed and focus coil current) has been investigated. The presence of typical zones with the energy spectrum peaks in the low-frequency and high- frequency bands has been shown. It has been established that the peak location in the high- frequency range of the energy spectrum does not depend on the welding modes and the position of the probes relative to the keyhole. The low-frequency range of the energy spectrum depends on the vapor flow density of the keyhole and is rather sensitive to the welding modes. The use of electron beam oscillation makes it possible to control plasma flows and hydrodynamic processes in the penetration channel.
Research of trends in the development of laser additive manufacturing in the Russian Federation on the basis of patent information
Authors: Somonov V V 
Published: November 2021

Abstract
The article presents the results of the analysis of patent documentation on laser additive manufacturing registered in the territory of the Russian Federation. As a result of the research, the dynamics of patent activity is determined, the top patent holders, the leading countries in the considered technological field are identified, the top of inventors is compiled, the main technological segments for application of patented solutions from the field of laser additive manufacturing are identified.
Study of the operating modes of the electrostatic lens of the welding electron gun
Authors: Titarev E K , Goncharov A L , Kharitonov I A , Davletshin A I 
Published: November 2021

Abstract
The paper presents the results of a study of the operating modes of a technological electron gun used in installations for electron beam welding. The design of an electron gun, which is part of the ELA-15I power complex, is considered, and the results of modeling the accelerating gap for a new design gun with an accelerating voltage of 120 kV are presented. The current-voltage characteristics of the gun operation were experimentally obtained at different temperatures of the main LaB6 cathode. For this, the beam current was recorded at different values of the control electrode potential. A mathematical model of the accelerating gap was implemented, which makes it possible to analyze the shape of the electron beam in the region of the first lens. Using a mathematical model, the shapes of the electron beam were calculated for various operating modes of the gun, and the characteristic transverse size of the beam in the crossover was determined. The beam diameter and the angle of convergence in the area of focusing the beam on the product were determined experimentally. Conclusions were made about the equality of the crossover diameters of the full-scale and mathematical models, as well as about the sufficient coincidence of the experimental and calculated volt-ampere characteristics. The design of the accelerating gap of the ELA-15 gun was optimized with an increase in the accelerating voltage from 60 kV to 120 kV. The optimization results are shown for the original and modified design in the form of a comparison of the patterns of the distribution of the electrostatic field strength and a comparison of the current-voltage characteristics.
Research on optimization of manned robot swarm scheduling based on ant-sparrow algorithm
Authors: Gao Qingji , Zheng Jiguang , Zhang Wencai 
Published: November 2021

Abstract
Considering the optimization problem of manned robot swarm scheduling in public environment, we constructed a demand-time-space-energy consumption scheduling model taking passenger waiting time and robot swarm energy consumption as optimization goals. This paper proposes an ant-sparrow algorithm based on the same number constraints colonies of ant and sparrow, which combines the advantages of ant colony algorithm great initial solution and the fast convergence speed of the sparrow search algorithm. After a limited number of initial iterations, the ant colony algorithm is transferred to the sparrow search algorithm. In order to increase the diversity of feasible solutions in the later stage of the ant-sparrow algorithm iteration, a divide-and-conquer strategy is introduced to divide the feasible solution sequence into the same small modules and solve them step by step. Applying it to the manned robot swarm scheduling service in the public environment, experiments show that the ant-sparrow algorithm introduced with a divide-and-conquer strategy can effectively improve the quality and convergence speed of feasible solutions.
Quantum rebound attack to D-M structure based on ARIA algorithm
Authors: Dou Shanque , Mao Ming , Li Yanjun , Qiu Dongying 
Published: November 2021

Abstract
With the increasing application of quantum computing, quantum technology is increasingly used in the security analysis and research of multiple symmetric cryptographic algorithms such as block ciphers and hash functions. In 2020, Sasaki et al. proposed a dedicated quantum collision attack against hash functions in EUROCRYPT. Some differential trajectories with a probability of 2−2n/3
that cannot be used in the classical environment may be used to launch collision attacks in the quantum environment. The ARIA algorithm is a block cipher proposed by the Korean researcher Kwon et al. on ICISC 2003. The block cipher algorithm is similar to AES in structure. This article mainly analyzes the security of Davies-Meyer structure, and uses AIRA as the permutation function to construct ARIA hash function based on the DM hash model. A new AIRA differential path was found based on MILP, and 7 rounds of ARIA-DM hash function quantum rebound attacks were given.
Determining the Rolling Window Size of Deep Neural Network Based Models on Time Series Forecasting
Authors: Shen Li , Wei Zijin , Wang Yangzhu 
Published: November 2021

Abstract
Time series forecasting has always been a significant task in various domains. In this paper, we propose DeepARMA, a LSTM-based recurrent neural network to tackle this problem. DeepARMA is derived from an existing time series forecasting baseline, DeepAR, overcoming two of its weaknesses: (1) rolling window size determination: the way DeepAR determines rolling window size is casual and vulnerable, which may lead to the unnecessary computation and inefficiency of the model;(2) neglect of the noise: pure autoregressive model cannot deal with the condition where data are composed of various kinds of noise, neither do most of time series models including DeepAR. In order to solve these two problems, we first combine a classic information theoretic criterion, AIC, with the network to determine the proper rolling window size. Then, we propose a jointly-learned neural network fusing white Gaussian noise series given by ARIMA models to DeepAR’s input. That is exactly why we name the network ‘DeepARMA’. Our experiments on a real-world dataset demonstrate that our improvement settles those two problems put forward above.