bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of AGV Control Strategy in a Processing System
Authors: Zhou Ling , Zhang Shengjie , Cai Ningyuan 
Published: November 2021

Abstract
A typical manufacturing system requiring a high degree of automation usually includes warehouse, AGV, CNC, assembly line and laser marking equipment. Among them, AGV plays an important role on the overall operating quality and operating efficiency. This paper studies AGV control strategy under the background of the typical manufacturing system. Firstly the two modes of AGV motion path are defined; the flow chart of AGV movement between any two points in the system is analyzed, and the AGV communication module in the minimum operation mode is designed; finally, control programs for several main scenarios are proposed based on PLC ladder diagram. The outcome helps the optimization of AGV control decision relating to a bottom operation layer of any manufacturing system.
Battery life prediction method based on DE-GWO-LSTM
Authors: Shi Yongsheng , Ren Jiarui , Shi Mengzhuo , Li Jin , Zhang Kai 
Published: November 2021

Abstract
Aiming at the problem of inaccurate prediction results of lithium-ion battery life, a lithium-ion battery life prediction model based on hybrid algorithm is designed. The position of grey wolf algorithm is updated by differential evolution algorithm, which improves the population diversity and avoids premature stagnation of the algorithm. The GWO-LSTM model and DE-GWO-LSTM model are compared and analyzed by using NASA data. The proposed DE-GWO-LSTM can well conduct global search and local search, and improve the prediction performance to a certain extent.
The synthesis of ReS2 flakes and its application in photodetectors
Authors: Xie YueLin , Chen Tingxuan , Chen Jian , Zhu Ling 
Published: November 2021

Abstract
ReS2 is attracting much attention because of its stable trion state. This kind of stable trion state arises on account of weak interlayer coupling as well as anisotropic crystal structure. In this research, we have synthesized ReS2 flakes successfully by using chemical vapor deposition (CVD) method. Stable ionic states in hexagonal wafers are observed by photoluminescence spectroscopy (PL). This substance is stable at room temperature. The HRTEM image from the single ReS2 hexagon reveals that the individual hexagon is single crystal. EDS spectroscopy indicates the purity of the synthesized product. We find that the Re and S atoms ratio in pure ReS2 is 1:2. Then we fabricate a photo detector on individual ReS2 flakes and test its performance. We compare the photocurrent in dark current and under a 500 nm incident light for two media (air and 100 ppm H2). Emission current increases from 1.15 μA to 1.67 μA (forward) and from 7.9 μA to 13.8 μA (reverse). Therefore, the ReS2 hexagonal wafer is an ideal choice for stable and reliable room temperature optical gas sensor. And the material can also be used for fast switch.
Research progress of silicon nanostructures prepared by electrochemical etching based on galvanic cells
Authors: Yang Xiaoyu , Tong Ling , Wu Lin , Zhang Baoguo , Liao Zhiyuan , Chen Ao , Zhou Yilai , Liu Ying , Hu Ya 
Published: November 2021

Abstract
Metal-assisted etching of silicon in HF aqueous solution has attracted widespread attention due to its potential applications in electronics, photonics, renewable energy, and biotechnology. In this paper, the basic process and mechanism of metal assisted electrochemical etching of silicon in vapor or liquid atmosphere based on galvanic cells are reviewed. This paper focuses on the use of gas-phase oxidants O2 and H2O2 instead of liquid phase oxidants Fe(NO3)3 and H2O2 to catalyze the etching of silicon in the vapor atmosphere of HF aqueous solution. The mechanism of substrate enhanced metal-assisted chemical etching for the preparation of large-area silicon micro nanostructure arrays is summarized, and the impact of substrate type and surface area on reactive etching is discussed.
Research progress of Pt-based electrocatalysts for the cathode of proton exchange membrane fuel cells
Authors: Wu Jing , Wang Haibin , Cong Yuanyuan 
Published: November 2021

Abstract
Research on advanced platinum (Pt)-based electrocatalysts has an important impact on proton exchange membrane fuel cells. This review introduces the current research progress of Pt-based electrocatalysts for oxygen reduction reaction (ORR) and puts forward the problems that need to be solved in future development.
Preparation and properties of ice cream flowers Ce/TiO2 photocatalyst
Authors: Fang Qi , Ou Xiaoxia , Yang Xiaoyu , Zhao Ke , Zhang Fengjie , Liang Chunyang 
Published: November 2021

Abstract
TiO2 composite photocatalysts with doping amounts of Ce (0.5%Ce/TiO2, 1%Ce/TiO2, 2%Ce/TiO2, 3%Ce/TiO2 and 5%Ce/TiO2)were synthesized via a sol-gel method.The structure and morphology of the prepared composites were characterized by XRD, SEM, DRS, XPS. At the same time, the photocatalytic effect of the composite on rhodamine B (RhB) solution under simulated visible light irradiation was explored.The results indicated that the crystal of powder catalyst was anatase type TiO2, and the directional aggregation of Ce/TiO2 composite photocatalyst showed ice cream flowers-shaped structure.The photocatalysis activity was the best when Ce doping amounts were 3%.The degradation rate of RhB was 96% in 120 min, which was 50% higher than pure TiO2.Hydroxyl radical (⋅OH) played a leading role in the whole photodegradation reaction system, and its contribution rate was about 66.4%.
The process for preparing MX2 (M=Mo,W; X=Se,S) single crystal
Authors: Zhang Xiaoli , Zhang Xiaoyi , Yang Yu 
Published: November 2021

Abstract
The layered semiconductor compound, as transition metal dichalcogenide family MX2 (M=Mo, W, X=S, Se) had stirred common interesting in solar energy conversion for its special photoelectronic properties. The synthesizing of its single crystal free of surface defects is a pressing matter of the moment. In this paper, the key points in preparing such single crystal are concluded, that is high vacuum, long time, and small ΔT, sometimes the transport agents have to be used to help the matter diffusion. And the proper quantities of these parameters are detailed in this paper too.
Simulation of crystal plasticity of P92 heat resistant steel considering martensitic lath structure
Authors: Wang Xinyu , Shen Junjie , Guo Xiangru , Qiao Jixin 
Published: November 2021

Abstract
Based on the theory of crystal plasticity, coupled with dislocation and lath hardening models, this paper establishes a crystal plasticity finite element model describing the high temperature creep of P92 steel. Open source software was used to generate lath models with an average size of 350nm, 650nm and 950nm to explore the effect of lath coarsening on the high-temperature creep behavior of P92 steel. The results show that the roughening of the slats increases the rate of creep deformation, resulting in a decrease in the service life of the material. Observing the slat model, it can be seen that the roughening of the slats enlarges the numerical gradient of stress and strain, and aggravates the overall plastic strain of the model. The coarsening of the slats accelerates the movement of dislocations, causing the density of movable dislocations to increase, and at the same time the shear strain amplitude of the slip system increases, thereby reducing the hardening behavior of the material.
The preparation of Li7La3Zn2O12(LLZO) battery ceramic and its conductivity
Authors: Zhang Xiaoli , Zhang Xiaoyi , Yang Yu , Duan Jiawei , Mi Liwei 
Published: November 2021

Abstract
For Li7La3Zr2O12 (LLZO) solid electrolytes, higher density usually means higher ionic conductivity. Researchers tried many preparation methods to get high density samples and at same times to realize industrial production, low cost, scalable and fast synthesis techniques. In this paper, the mainstream preparation methods of LLZO was given, as polymerized complex method, sol-gel method, field assisted sintering, combustion technique, auto-consolidation method, water-based solvent method. Among these methods, the last four methods can always increase the density to more than 93%. Especially the field assisted sintering method can make the relative density to be high as 99.8%. And all of these methods can make the ion conductivity to be higher than 1.4 × 10-4 S cm-1. Also, most of these methods introduced the Al element into LLZO to realize the liquid sintering.
Determination of 9 kinds of volatile halogenated alkane and chlorobenzene compounds in water by gas chromatography-mass spectrometry with purge and trap method
Authors: Liu Yanqin 
Published: November 2021

Abstract
In this study, in the face of water environmental pollution, a more simple and efficient detection method was obtained for simultaneous determination of 9 kinds of volatile halogenated alkane and chlorobenzene compounds in water by PT/GCMS. By optimizing the purge and trap conditions, the optimal experimental conditions were obtained as follows: purge time was 15 min, purge temperature was 35 °C, purge velocity was 40 mL/min, desorption time was 2 min, desorption temperature was 240 °C. The linearity of the method was good, and the correlation coefficients were all greater than 0.999. The minimum detection limit(MDL) of the method was 0.1 μg/L. The average recovery rate ranged from 85.4 %~102.1 % in surface water and drinking water with relative standard deviation (RSD) ranged from 5.3 %-9.2 % in the spiked concentration levels of 5 μg/L and 10 μg/L. This method has the advantages of simple operation, good separation effect, rapid detection, high recovery and good precision, and can simultaneously meet the requirements of 9 kinds of volatile organic compounds detection in drinking water and surface water. This work provides a new method for the detection of volatile organic compounds in water and will have great significance for the detection of water quality.
C(sp3)-H alkenylation promoted by uranyl cation as a visible-light photocatalyst
Authors: Feng Zhiyu 
Published: November 2021

Abstract
The alkenylation of cyclic ethers with β-nitroalkenes using uranyl cation as a photocatalyst is reported. Previous studies revealed the feasibility of incorporating organic photocatalyst in the visible light mediated alkenylation, while the uranyl cation serves as an alternative photocatalyst candidate successfully accomplish this transformation through a different pathway. The reaction features the direct hydrogen atom transfer (HAT) process to activate alpha C(sp3)-H of cyclic ether, and consequently cyclic ether is coupled with β-nitroalkene to give the target product with F-selectivity through C-C bond formation.
Effect of pulse frequency on laser welding on SiCp/6061 aluminum alloys with powder
Authors: Jian Yongchao , Shi Yan 
Published: November 2021

Abstract
Because of the uneven distribution of reinforcement particles in the molten pool during laser welding of SiCp/6061Al composites with powder, the effect of pulse frequency on the homogenization was studied in this paper. The pulse frequency of welding is changed and the macro morphology of the weld is studied by metallographic microscope. The particle uniformity of reinforcing phase and the porosity of molten pool at different frequencies were compared. The tensile strength of welded joints at different frequencies was tested by universal tensile machine. Finally, when the pulse frequency is 160Hz, the particle distribution of reinforcing phase is the most uniform and the tensile strength is the largest. The tensile strength reaches 267.06MPa, reaching 69.1% of the base metal. When the pulse frequency is 320Hz, the porosity of the weld is the lowest, reaching 1.75%.
Performance of multi-antenna wireless systems based on time reversal
Authors: Shen Aiguo , Yang Guangsong , Wei Dezhi 
Published: November 2021

Abstract
5G wireless mobile communication system is faced with massive equipment access, information security and effective transmission is worth paying attention to. Wireless physical layer security mainly uses encryption principle to enhance the security of information transmission, while time reversal technology combines its electromagnetic characteristics and physical channel characteristics to improve the security performance of wireless communication system. In this paper, a signal transmission model of wireless multi-antenna communication system based on time reversal cavity is proposed and white Gaussian noise is introduced. The simulation results show that the space-time focusing characteristics of time reversal cavity can make the signal energy more concentrated on the target user, which can not only effectively alleviate the communication quality problems caused by multipath effect, but also ensure the security of information transmission process.
RETRACTED: Quality Inspection of Digital Archives of Application and Installation in Power Business Expanding based on Artificial Intelligence Technology
Authors: Liang Haihong , Zeng Ling , Shen Xiaozhou , Shi Weiwei , Cang Jiujiao 
Published: November 2021

Abstract
The existing quality detection methods of business expansion digital archives have the problem of fuzzy evaluation standard, which leads to low classification accuracy. This paper designs a quality detection method of business expansion Digital Archives based on artificial intelligence technology. The business characteristics of business development are extracted, the minimum business data unit is described, the digital archive catalogue database is established, the digital archive evaluation standard is defined, the text similarity is calculated, the user model is established, and the quality inspection mode is established by using artificial intelligence technology. Experimental results: the average classification accuracy of the designed method based on artificial intelligence technology and the other two quality detection methods is 55.763, 43.560 and 42.605, which proves that the quality detection method based on artificial intelligence technology has higher use value.
Smart Bluetooth beacon based on LoRa Positioning method and system research
Authors: Su Rui , Dai Yawen 
Published: November 2021

Abstract
In the era of the Internet of Everything, applications based on real-time location continue to appear in various industries. The indoor and outdoor positioning, analysis and management of personnel and objects can effectively improve the efficiency of production and management, which is of great significance to many industries. The use of Bluetooth beacon positioning has the advantages of low energy consumption, low cost, and fast data transmission speed. However, in real life, there are two obstacles to receiving signals, which are easily affected by the environment and the need for frequent on-site maintenance. This paper designs and implements a new type of LoRa-based smart Bluetooth beacon, which can be quickly connected to LoRa. Online monitoring and remote control can achieve better adaptation to the environment, and can fit a better signal attenuation model in the deployment environment in real time. Traditional signal strength positioning solutions have their own limitations. In order to improve the positioning accuracy of the Bluetooth beacon and the universality of the algorithm, in view of the low deployment density of beacons, the positioning accuracy is not good and the anchor circle has various situations, an optimized weighted centroid positioning scheme integrating greedy strategy is proposed.
Deep Reinforcement Learning for Channel Selection and Power Allocation in D2D Communications
Authors: Zhou Jun 
Published: November 2021

Abstract
Device-to-device (D2D) communication is regarded as a key technical component of the fifth-generation (5G), D2D communication usually reuses spectrum resources with cellular users (CUs). To mitigate interference to cellular links and improve spectrum efficiency, this paper investigates a sum-rate maximization problem in the underlay of D2D communication. Particularly, a joint channel selection and power allocation framework based on multi-agent deep reinforcement learning is proposed, named Double Deep Q-Network (DDQN). It can adeptly select the channel and allocate power in a dynamic environment. The proposed scheme only requires local information and some outdated nonlocal information, which reduces signaling overheads significantly. Simulation results show that the proposed scheme can improve the D2D sum rate and ensure quality-of-service (QoS) of CUs compared with other benchmarks.
Multi-mode Network Analysis under Differential Privacy
Authors: Song Yuning , Ding Liping , Dong Mengying , Liu Xuehua , Wang Xiao 
Published: November 2021

Abstract
With the advent of the big data era and the advancement of social network analysis, the public is increasingly concerned about the privacy protection in today’s complex social networks. For the past few years, the rapid development of differential privacy (DP) technology, as a method with a reliable theoretical basis, can effectively solve the key problem of how to “disassociate” personal information in social networks. This paper focuses on the multi-mode heterogeneous network model which has attracted a lot of attention in the field of network research. It introduces differential privacy and its application in big social networks briefly first, and then proposes a centrality-analysis method based on DP in a typical social network, i.e. the multi-mode network. The calculation principle and applicable scenarios are discussed. Then, its utility is analyzed and evaluated through experimental simulation. Possible improvement of DP algorithm in multi-mode networks above is prospected in the end.
Application of Improved Sparrow Search Algorithm in Concrete
Authors: Ouyang Chengtian , Tang Feng , Zhu Donglin , Qiu Yaxian , Liu Yujia 
Published: November 2021

Abstract
Compared with other algorithms, the performance of sparrow algorithm is better, but it also has shortcomings such as insufficient convergence and large randomness. For this reason, this paper proposes an improved sparrow search algorithm, which uses K-means to initialize the population to reduce the influence of randomness. Use sine and cosine search to improve the quality of the position of followers, and finally use adaptive local search to update the optimal solution, and apply it to concrete strength prediction. The results show that various improved sparrow search algorithms have certain advantages and high stability.
Research on VANET vehicle movement modeling in ITS
Authors: Wei Yun , He Zhaohui 
Published: November 2021

Abstract
At present, Traffic simulation has become the most widely used tool in operational research and system analysis. This paper studies VANET’s vehicle movement modeling theory in the Intelligent Transportation System. It build Car movement model by OPNET Modeler soft. It simulates VANET communication process, evaluates the entire performance of the network, which can offer reference to designing and optimizing the Vehicle Ad hoc Network.
An Algorithm for Automatically Extracting Dental Arch curve
Authors: Zhu Shengshan , Fang He , Zhang Dawei 
Published: November 2021

AbstractDental cone beam CT (CBCT) scans, due to their low radiation dose, are now widely used in the medical diagnosis of patients’ oral cavity. The reconstruction of a panoramic view of the dental arch from the scanned CBCT data facilitates the dentist’s observation of the patient’s oral condition. The most important technique for reconstructing the dental arch panorama is the extraction of the dental arch curve accurately. The existing method is to rely on the experience of the dentist to manually connect the dental arch curve, or use techniques related to threshold segmentation to extract dental arch curve. These methods rely on the experience of dentists on the one hand. On the other hand, when there are interferences such as implants, metal tubes, braces or missing teeth in the patient’s mouth, the threshold calculation will be wrong. Based on this, this article starts with the histogram of CBCT data, and proposes a highly robust and fully automatic dental arch curve extraction method. In the actual experiment, the dental arch curves of 40 different patients were extracted, and all the dental arch curves can be accurately and automatically extracted, thus verifying the effectiveness of the proposed algorithm.
LinGAN: an Advanced Model for Code Generating based on Linformer
Authors: Dai Hongming 
Published: November 2021

Abstract
Parsing natural language to corresponding programming language attracts much attention in recent years. Natural Language to SQL(NL2SQL) widely appears in numerous practical Internet applications. Previous solution was to convert the input as a heterogeneous graph which failed to learn good word representation in question utterance. In this paper, we propose a Relation-Aware framework named LinGAN, which has powerful semantic parsing abilities and can jointly encode the question utterance and syntax information of the object language. We also propose the pre-norm residual shrinkage unit to solve the problem of deep degradation of Linformer. Experiments show that LinGAN achieves excellent performance on multiple code generation tasks.
A new data classification improvement approach based on kernel clustering
Authors: Guo Bingsen 
Published: November 2021

Abstract
Data classification is one of the most critical issues in data mining with a large number of real-life applications. In many practical classification issues, there are various forms of anomalies in the real dataset. For example, the training set contains outliers, often enough to confuse the classifier and reduce its ability to learn from the data. In this paper, we propose a new data classification improvement approach based on kernel clustering. The proposed method can improve the classification performance by optimizing the training set. We first use the existing kernel clustering method to cluster the training set and optimize it based on the similarity between the training samples in each class and the corresponding class center. Then, the optimized reliable training set is trained to the standard classifier in the kernel space to classify each query sample. Extensive performance analysis shows that the proposed method achieves high performance, thus improving the classifier’s effectiveness.
Direction reconstruction using a CNN for GeV-scale neutrinos in IceCube
Authors: Yu S. 
Published: November 2021

Abstract
The IceCube Neutrino Observatory is designed to observe neutrinos interacting deep within the South Pole ice sheet. It consists of 5160 digital optical modules, which are arrayed over a cubic kilometer from 1450 m to 2450 m depth. At the lower center of the array is the DeepCore subdetector. It has a denser configuration which lowers the observable energy threshold to about 10 GeV and creates the opportunity to study neutrino oscillations with low energy atmospheric neutrinos. A precise reconstruction of neutrino direction is critical in the measurements of oscillation parameters. In this contribution, I will discuss a method to reconstruct the zenith angle of 10-GeV scale events in IceCube using a convolutional neural network and compare the result to that of the current likelihood-based reconstruction algorithm.