bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tuning the optical and electrical properties of HiPIMS-ITO films by variation of annealing temperature
Authors: Zhang Jin-Fa , Zhao Ming-Jie 
Published: June 2022

Abstract
High power impuls magnetron sputtering (HiPIMS) deposits high quality films due to high ionization fraction. In this work, Indium tin oxide (ITO) films are deposited by HiPIMS methord. The effects of annealing temperature under nitrogen environment on the crystal structure, optical properties and electrical properties of ITO films were investigated. The properties of the films were characterized by atomic force microscopy (AFM), X-ray diffraction (XRD), Hall measurement system (Hall), and UV-Vis spectrophotometer. The results showed that the average visible transmittance of the annealed ITO film reached 83.5%. The XRD results show that the ITO film grain size slightly increased after annealing. The mobility increases after annealing. This study proves that HiPIMS deposited ITO thin film is very superior to low temperature processing, and the grown thin film can be used in LEDs and solar cells.
LIDAR–camera deep fusion for end-to-end trajectory planning of autonomous vehicle
Authors: Zhang Yilin 
Published: June 2022

Abstract
Lidars and cameras are critical sensors which offer complementary information for scene perception and trajectory planning tasks in autonomous driving. In this work, we propose an attention-based framework to integrate representations of information from the two sensors and complete trajectory planning tasks using an end-to-end learning-based approach. To fuse 3D point cloud with RGB image in the same dimension, we also utilize a gradient transformation operation to convert point cloud into grey images. For the trajectory planning task, we use an auto-regressive network consisting of GRUs to predict future trajectory of ego-vehicle. The experiment results show that the proposed framework outperforms the models with single sensor input and the model without cross attention. We demonstrate the efficacy of our approach in the CARLA driving simulator.
High-precision velocity measurement method based on high frame rate image processing
Authors: Zhou Saiao , Nie Yuman , Fan Fan , Tang Yuanyang , Wang Zhou , Wang Lingfei , Wang Yaoxiong , Cao Pingguo 
Published: June 2022

Abstract
The traditional drop-weight impact velocity measurement is affected by the measurement distance of the sensor and the measurement environment, and the accuracy is difficult to guarantee. Aiming at this problem, this paper proposes a high-precision velocity measurement method based on high frame rate image. Firstly, a measurement scheme based on high frame rate image is designed, the position information is obtained by processing the image of the marked point, and the target impact velocity is obtained according to the time difference between frames; Then an error model is established, and the sources of errors and solutions are analyzed; Then by improving the subpixel edge and other methods to improve the feature extraction accuracy of the marking point image, thereby improving the velocity measurement accuracy. Finally, the measurement accuracy is verified by the actual drop-weight free-fall experiment. The experimental results show that the method proposed in this paper is better than 0.5% in the measurement of the impact velocity of the drop weight, which meets the needs of practical applications, and the measuring process is visualized and traceable, which has high application value.
Research on target localization and recognition based on binocular vision and deep learning with FPGA
Authors: Jiang Peijing , Luo Li , Zhang Bixuan 
Published: June 2022

Abstract
Agricultural picking robots have ushered in a good development period, and the research on the related technologies is becoming more and more practical. Based on this, this paper designs a crop identification and localization method based on binocular vision and deep learning supplemented by FPGA hardware platform. This paper firstly introduces the necessity of the technology for recognition and localization, then introduces the theoretical knowledge of camera calibration, stereo matching, and convolutional neural networks, etc. Finally, the implementation of relevant algorithms and the system architecture model are carried out. The method designed in this paper can provide technical support for agricultural picking robots, which can contribute to the development of picking robots.
Soybean image segmentation based on multi-scale Retinex with color restoration
Authors: Lin Wei , Lin Yu 
Published: June 2022

Abstract
Aiming at the matter of seed overlapping and adhesion within the actual quality detection of soybean, a soybean image segmentation based on multi-scale Retinex with color restoration (MSRCR) was proposed. Firstly, original images of soybean were obtained by the industrial camera. secondly, these images were enhanced by MSRCR. Thirdly, these images after MSRCR were segmented by Otsu. Finally, soybean seed images were extracted by mask and minimum bounding rectangle from soybean images after MSRCR. The image acquisition system was constructed and the algorithm was verified. The experiment showed that the segmentation accuracy of the proposed algorithm was 98.05%, which can meet the requirement of soybean image segmentation. Additionally, the proposed algorithm can also provide an image preprocessing method for agricultural seed classification in similar scenes.
Design of Mobile Phone Automatic Assembly System Based on Machine Vision
Authors: Yuan Fei , Shen Xiaozhong , Wu Jiawei , Wang Lihui 
Published: June 2022

Abstract
In the four links of mobile phone production, assembly employees account for 60%. In order to improve the assembly efficiency of mobile phone, this paper designed a mobile phone automatic assembly system based on machine vision. The system mainly includes PLC control system, mechanical arm, vision system and touch screen. SIMATIC S7-1200 CPU 1214C is used as PLC controller, and control program is designed.The mobile phone shell, mobile phone chip and screen panel are captured and assembled by DOBOT MG400 four-axis mechanical arm of Yuejiang Technology. Hikvision’s products are selected as the hardware of the vision system, and vision program is designed using DobotVisionStudio algorithm platform of Yuejiang Technology. Vellon’s MT6071IP/MT8071IP (800×400) is the touch screen for the system, and through it, the system can be manually controlled and monitored. Practice has proved that the mobile phone automatic assembly system designed in this paper can perfectly complete the whole process of mobile phone assembly, and the success rate is more than 99%.The mobile phone automatic assembly system based on machine vision has high success rate, high stability, labor saving and long-term operation, which has a certain practical reference significance.
Reformatted contrastive learning for image classification via attention mechanism and self-distillation
Authors: Duan Jiayi 
Published: June 2022

Abstract
Image classification, a basic task for computer vision, is widely achieved using deep learning methods. Recently proposed contrastive learning has made a great progress to feature representation in self-supervised manner, which outperforms traditional contrastive loss, for instance, triplet loss and N-paired loss. In this paper, we propose a reformatted contrastive learning paradigm which is an extension of conventional self-supervised contrast learning. Specifically, multiple positive and negative pairs are constructed for each anchor, thus creating a link between the positive and negative factors. In addition to this, we employ a self-attention module in the network architecture with the aim of focusing on foreground pixels and building long-range dependencies across regions. We also present a self-distillation approach for fine-tuning the classifier using a well-trained feature encoder. which improves the generalization ability of our method. Experiments on CIFAR100 and CUB200-2011 reveal that our method outperforms rival methods, confirming the efficacy of our strategy.
Research on combined radio frequency fingerprint identification model with limited samples
Authors: Zhu Qingchao , Guo Qiqi , Song Xiaoou , Zhang Yue 
Published: June 2022

Abstract
Aiming to solve the real problem of civilian aircraft identification, a novel combined radio frequency fingerprint (RFF) identification model is proposed, consisting of data analyzing processing, standard characteristic parameter database establishment, classification and optimization. In data analyzing processing step, discrimination was realized for wavelet coefficients, instantaneous phase, Hilbert huang transform energy spectrum, coefficients, time field envelope, probability density function, on basis of which, characteristic parameters were confirmed. In standard characteristic parameter database establishment step, a standard database was found through direct measurement method to avoid losing the RFF feature. In classification step, single character assortment rule and combined classifying rule were defined, with correlative concept and threshold concept. Finally, optimization for the model was realized by modifying parameters manually. Results show that, though hardware was limited and amount of samples were fewer, average identification rate is near to 69.75 percent, providing a theoretical reference for the real problem of identifying different aircrafts.
Research on camouflage target detection method based on improved YOLOv5
Authors: Zhang Wei , Zhou Qikai , Li Ruizhi , Niu Fu 
Published: June 2022

Abstract
Objective: In the task of camouflage target detection, there is a problem that the target is highly integrated with the complex environment background, which is difficult to identify and leads to false detection and missed detection. A target detection algorithm CM-YOLOv5s is proposed for camouflage characteristics. Method: The algorithm uses YOLOv5s as the basic framework. First, a coordinated attention mechanism is embedded in the backbone feature extraction network, which enhances the network’s ability to extract camouflaged target features, weakens the attention to the surrounding background, and effectively improves the algorithm’s anti-background. Interference ability; secondly, the Mixup data enhancement strategy is used to simulate overlapping occlusion scenarios, which further strengthens the network model’s learning ability for complex samples. Results: The training and verification were carried out on the self-made Military Camouflage Target Dataset (MCTD), and the precision, recall, and average mAP of the improved CM-YOLOv5s algorithm reached 95.9%, 87.1%, and 94.1, respectively. %, compared with the original YOLOv5s model, the average accuracy rate is improved by 3.8 percentage points. Conclusion: The improved algorithm has better detection effect, and realizes accurate identification and rapid positioning of military camouflage targets in complex environments.
Operator Optimization Oriented Person Re-Identification
Authors: Cao Qichun , Wang Binqiang , Dong Gang , Hu Kekun , Yang Hongbin 
Published: June 2022

AbstractUsing FPGA to accelerate the application of convolutional neural networks has attracted more and more attention. However, the design technology of the FPGA accelerator cannot follow up the latest achievements of the convolutional neural networks, nor can it consider optimizing the complex network structure combined with the characteristics of hardware to improve the accuracy of the network and simplify the implementation of hardware. To address these issues, in this paper, we adopt the development idea of algorithm-hardware co-design, compress the structure and optimize the operator for a state-of-the-art lightweight person re-identification network, and design a new network model SGCNet (Shift Gaussian Convolution Network). Specifically, SGCNet is obtained by structure optimization and operator replacement according to the optimization degree of the operator in the FPGA hardware environment. For convolution operation, only 1 × 1 kernel convolution operator is adopted in SGCNet, while spatial convolution is replaced by a more effective shift operation. SGCNet is more concise and clear in the operation types and complex structure of the network. Experimental evaluations demonstrate that SGCNet’s top-5 accuracy of 92.7% on ImageNet and R1 accuracy of 74.6% on CUHK03 of person re-identification data set, is higher than CMSNet network.
Template Construction of Radar Target Recognition based on Maximum Information Profile
Authors: Cui Hao , Su Min , Liu Jia , Liu Lili 
Published: June 2022

Abstract
High resolution range profile (HRRP) has the advantages of low complexity in imaging and processing. These features make HRRP widely adopted in radar automatic target recognition technology. Template matching is a representative technique for radar target recognition using HRRP. To overcome the attitude sensitivity problem of HRRP data, it is necessary to subdivide the training database according to attitude domain, and construct corresponding templates for matching. However, templates from traditional methods usually cause the loss of details due to the smoothing process, with limited classification performance. This paper is motivated by proposing a template generation approach based on maximum information profile, which retains the detailed information in templates for accuracy optimization. The proposed method is verified by the recognition experiments of three types of aircraft targets. The experimental results indicate that the maximum information profile outperform the mean range profile contributed by the angle domain template.
Design of Pipe-inspection Robot Based on YOLOv3
Authors: Hu Zhangying , Zhou Jingang , Yang Benquan , Chen Aihua 
Published: June 2022

Abstract
In this paper, a pipe-inspection robot system which uses STM32F103 as control core is designed. The robot system adopts YOLOv3 network model to detect and locate defects of sewage pipeline. The robot uses closed-circuit television system for detection, which is composed of hardware and defect detection. The hardware is mainly composed of robot body, winding coil and upper computer. The motor drive module, body attitude sensor of robot and camera are placed in the pipeline robot. The router, lithium battery and length measurer constitute the winding coil, which is connected with the robot through cable for data transmission and power supply. the upper computer communicates with the cable coil through WIFI, and the staff can send various instructions through the upper computer to control robot operation, and view the status of the pipeline through video. The defect detection of pipeline is mainly realized by YOLOv3 network model, which is used to automatically detect the types of defects in sewage pipeline and mark the location of defects. Finally, the feasibility and effectiveness of defect detection based on YOLOv3 network model are verified by simulation experiments.
Effect of assembly margin on laser weld formation for niobium tungsten alloy
Authors: Xu Fei , Li Yulong , Zhao Xiaolong , Ma Cunqiang , Jiang Kuan 
Published: June 2022

Abstract
Based on the optimization experiment of laser welding process of niobium-tungsten alloy, the effects of assembly gap value and misalignment value on laser weld formation, microstructure and mechanical properties of Nb521 niobium-tungsten alloy were investigated by using variable gap method, equal gap method and equal misalignment value method. The results show that Nb521 niobium-tungsten alloy has good laser weldability. The maximum gap value margin of 1.0mm and 1.5mm thickness of base metal are about 22% and 10.6% of the base metal thickness, respectively. And the maximum misalignment value margin is about 30% and 33% of the base metal thickness, respectively. The welded joints are characterized by fine columnar crystal structure from the fusion zone to the center of the weld, and are little affected by assembly gap value and misalignment value. When the assembly gap value or misalignment value is not greater than the maximum margin, the welded joints are fractured in the base metal zone, which is far away from the weld. Therefore, the welded joints of Nb521 niobium-tungsten alloy by laser welding have excellent tensile mechanical properties at room temperature.
Research and Development of Organic/Inorganic Mixtures Compound Coated Antioxidants
Authors: Zhou Ningning , Yang Liancheng , Du Li , Wang Nannan , Qi Cheng 
Published: June 2022

Abstract
For plastic thermal oxidative aging, it is inevitable that the material properties will decline and eventually lead to product damage. It is very important to improve the performance retention rate of materials under aging conditions and ultimately delay the damage to prolong the service life of products. In this study, nano-zinc oxide was selected as the compound auxiliary antioxidant of the main antioxidant 1010. Nano-zinc oxide is very obvious to improve the comprehensive performance of plastics. The retention rate of the tensile strength and elongation at break of the plastic in the test is significantly improved after hot air aging due to the small size effect of nano-zinc oxide increases the cross-linked network density, which is related to the realization of molecular-level bonding of polymer materials. This study not only innovated in the selection of materials which selected nano-zinc oxide as an auxiliary antioxidant, but also realized the coating structure of the main/auxiliary antioxidant by changing the process conditions, so as to finally realize the ideal mixing and distribution of the main/auxiliary antioxidant, to improve the mechanical properties of general-purpose plastics after introduction, and ultimately optimize the antioxidant properties.
Research on the evaluation method of the Rheological Properties of Magnetorheological Grease
Authors: Lei Yulong , Hu Zhide , Jiang HaoYang , Zhao Hujun , Zhang Hansong 
Published: June 2022

Abstract
Research on the rheological properties of magnetorheological grease(MRG) is of great significance for evaluating its properties, revealing the internal parameters, and guiding its application. The characterization methods of rheological properties usually include steady-state shear mode and oscillatory shear mode. However, the experiment of MRG rheological properties is mostly carried out in steady-state shear mode. To characterize the rheological properties of different base oil -based magnetorheological greases, the adaptability of the steady-state shear mode is discussed, and the feasibility of using the oscillatory shear mode is analyzed. The evaluation parameters of the MRG rheological properties are studied.
Numerical Simulation on Stick-Slip Properties of Fault Considering Loading Velocity
Authors: Wang Wei , Xu Lanyu , Yao Rong 
Published: June 2022

Abstract
The stick-slip of faults is one of the main causes of earthquakes in tectonic earthquake. The traditional interface element model cannot simulate the stick-slip phenomenon in the fault sliding although it can simulate the change of stress field of the rock mass by the because of the fault. Based on the interface element in FLAC(Fast Lagrangian Analysis Continua), the friction law of the interface element of the fault is redeveloped by using the Fish language, which is embedded in the FLAC, and the rate-state dependent friction law is introduced into the interface element. The effects of loading rate on rock friction properties were investigated and compared with previous experimental results. Well consistency was obtained to further study the development and evolution of fault slip.
The effect of nodulation on the distribution of concentration and current density during copper electrolytic refining
Authors: Zhao Jingya , Meng Yi , Li Chun , Tie Jun 
Published: June 2022

Abstract
During the industrial copper electrolytic refining process, the suspended particles in the electrolyte are adsorbed on the surface of the cathode and form nodulations, leading to the disturbance of the normal state in the electrolyte. When nodulations grow and then contact with the anode, short circuits occurs. It reduce current efficiency and product quality. In this paper, the concentration and current density changes in the nodulation surface and the anode surface is proposed. The current density on the nodulation is the largest and the concentration is the smallest.
Analysis of the Reason for the Fracture of the Safety Valve Spring in the Anhydrous Hydrogen Fluoride Tank
Authors: Xi Lingli , Chen Wuchao , Chen Zheming , Mu YanChun 
Published: June 2022

Abstract
This paper analyzes the fracture of the safety valve spring of an anhydrous hydrogen fluoride tank in a logistics unit through macro inspection, chemical composition analysis, metallographic inspection, hardness measurement, electron microscope scanning analysis, and other technical means to find the reason for the fracture of the safety valve spring. In addition, effective preventive measures are put forward to reduce and prevent the occurrence of such problems and improve the safety of the use of tank containers.
Forced Vibration of Axially Accelerating three Parameter Beam Constituted by Fraction Alderivative Model
Authors: Niu Pengyu , Wang Bo 
Published: June 2022

Abstract
The forced vibration characteristics of axially variable speed viscoelastic beams are studied. The material is described by the three parameter model of Poynting-Thompson beam. According to Newton's second law, the fractional derivative is introduced to deduce the governing equation of the beam. The approximate analytical solution and amplitude frequency equation are obtained by multi-scale method. The amplitude frequency equation is divided into real part and imaginary part by separating variables. According to the Routh-Hurwitz criterion, the Jacobi matrix and characteristic equation are established to determine the stable region and unstable region obtained under different parameters. Numerical examples show that the instability region shows a downward trend with the increase of the order of fractional derivative.
Comparative research on tension-compression mechanical properties of the azide propellant
Authors: Wu Weijing , Li Haiyang , Shen Zhibin , Fan Zijian 
Published: June 2022

Abstract
While the azide propellant is a typical particle-reinforced composite material, its mechanical properties are quite different under two different loads of tension and compression. In order to study the possible relationship between the tension and compression mechanical properties of the propellant, so as to further study the loading mechanism of the propellant, this paper carried out constant-rate tension and constant-rate compression tests of the azide propellant and measured the stress-strain curves in different loading case for follow-up comparative study. The mechanical properties of the propellant under different loading rates were analyzed quantitatively, and the differences between the tension and compression stresses of the propellant at different strain rates were quantitatively analyzed, and the change rules of tension-compression mechanical properties of the azide propellant were obtained. The research results can provide the basis for the application analysis of the azide propellant in the engine, and the research method can provide a reference for the tension-compression comparative study of other types of propellants.