bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physics Edutainment Learning based on Engklek and Ontang-Anting Games: Creating Fun Physics for Students
Authors: Hariyono E , Rizki I A , Rizqillah I A , Citra N F , Shobah N , Zainuddin A 
Published: December 2022

Abstract
This study aims to describe students' responses to edutainment-based physics learning. The study was conducted with a qualitative approach involving 33 pre-service physics teachers. The data were analyzed using Miles and Huberman's model, including data reduction, data display, and conclusion drawing. The results showed that 52% of pre-serviceteachers did not know the existence of edutainment-based physics learning as a learning instrument to create exciting and fun physics learning. However, most pre-service physics teachers choose numbers from 7 to 10 to indicate their level of agreement for edutainment-based physics learning. This means that most pre-service physics teachers agree that traditional Engklek games and Ontang-anting are applied to learn physics based on edutainment physics.
Segmentation Effect on Lungs X-Ray Image Classification Using Convolution Neural Network
Authors: Khoiro M , Firdaus R A , Suaebah E , Yantidewi M , Dzulkiflih  
Published: December 2022

Abstract
The effect of segmentation on lung X-ray image classification has been analyzed in this study. The 150 lung x-ray images in this study were separated into 78 as training data, 30 as validation data, and 42 as testing in three categories: normal lungs, effusion lungs, and cancer lungs. In pre-processing, the images were modified by adaptive histogram equalization to improve image quality and increase image contrast. The segmentation aims to mark the image by contouring the lung area obtained from the thresholding and some morphological manipulation processes such as filling holes, area openings, and labelling. Image classification uses Convolutional Neural Network (CNN) with five convolution layers, an Adam optimizer, and 30 epochs. The segmentation effect is analyzed by comparing the classification performance of the segmented and unsegmented images. In the study, the unsegmented X-ray image dataset classification reached an overall accuracy of 59.52% in the network testing process. The segmented X-ray image dataset obtained greater accuracy, 73.81%. It indicated that the segmentation process could improve network performance because the input pattern of the segmented image is easier to classify. Furthermore, the segmentation technique in the study can be one of the alternatives to developing image classification technologies, especially for medical image diagnosis. Segmentation Effect on Lungs X-Ray Image Classification Using Convolution Neural Network.
Pascal or Archimedes: Which Misconception is Higher?
Authors: Irawati R K , Sofianto E W N , Assidiqi H , Rahmawati I 
Published: December 2022

Abstract
The purpose of this research was to know the higher misconception between Pascal's law and Archimedes' law. The research method was qualitative descriptive. The question analysis is used to know the misconception using the four-tier test. The research subject was senior high school students in South Borneo with the purposive sampling technique. The object of this research was the senior high school students who had received the fluid static material. The result of the research showed that Archimedes' Law Material was the material with higher misconception than Pascal's law. The misconception of Archimedes' law had 51.62%, and Pascal's law at 20.52%. The implication of this research was to determine suitable learning on the Archimedes Law learning.
Correlation study between chaos features of physiological signals and emotions based on the information gain method
Authors: Nie Chunyan , Wang Huiyu 
Published: December 2022

Abstract
Clarifying the correlation between the chaos features of physiological signals and emotions plays an important role in improving the accuracy of emotion recognition. In this paper, the correlations of chaos features such as Lyapunov exponent, complexity, box dimension, and approximate entropy of physiological signals with positive, negative, and neutral emotions are analyzed and studied using the information gain method. Based on this, the Bagging-CHAID model is used for emotion recognition validation analysis. The results show that (1) the approximate entropy of physiological signals has the greatest correlation with positive, negative, and neutral emotions, followed by complexity and Lyapunov exponent features, and box dimensional features have the least correlation with the three emotions, thus, the approximate entropy can be chosen to improve the emotion validated based on Bagging-CHAID model, which showed the accuracy of the correlation analysis.
Study on Process Parameters of Low-power Semiconductor Laser Stripping PTFE Insulating Layer of Aviation Wire
Authors: Li Pin , Huang Huiping , Wang Ping , Huang Guangwen , Zhou Peimin , Tian Chunlin 
Published: December 2022

Abstract
Faced with the increasingly high-quality requirements for the insulation layer stripping at the end of aviation wires, laser wire stripping technology is becoming more and more popular due to its good processing quality and production efficiency. Traditional laser wire strippers generally have problems of bulky size and high control cost and are not suitable for the decentralized processing of large wire harness products. This work explores the feasibility of using a low-power semiconductor laser to strip the PTFE insulating layer of aviation wires. The influence of the parameter changes of each processing factor on the cut morphology of the insulating layer was studied separately. It was found that higher laser power removed more insulating layers per unit of time, but reduced the cutting quality. High laser scanning speed can obtain good insulation cutting quality, but too large or too small scanning speed will reduce the stripping efficiency. Simultaneous improvements in insulation cutting quality and efficiency depend on the right mix of power and scanning speed.
Development of Special Geomagnetic Data Acquisition System with Low Cost
Authors: Sun Hong-zhi , Zhao Lei , Yang Zhen-peng , Ren Xue , Luo Fei , Sun Yi-mei , Wang Qi , Gong Fei 
Published: December 2022

Abstract
It is known to all that the wide monitoring of geomagnetic anomalies requires geomagnetic detection equipment to be of low cost, low power, and high stability. On the basis of the weak magnetic signal detection technology, a weak magnetic signal acquisition system with low-cost magnetic data acquisition, data processing, and data analysis is established by using a three-dimensional SEN-R65 magnetic sensor, magnetic signal acquisition chip PNI 11096, and P89C668 chips. Firstly, the hardware of a low-cost geomagnetic data acquisition system is designed, and the corresponding data processing and analysis programs are written. Based on the designed hardware circuit and data processing for functions such as acquisition, transmission, storage, and real-time display of geomagnetic signals, it is found that the developed instrument meets the expectations of the low-cost geomagnetic data acquisition system designed in this paper, indicating that the system is applicable.
A Novel Interpolation Method for Cutting Trajectories in Spatial Coherent Cutting Machine
Authors: Wang Dewu , Zhang Cheng , Xi Xin 
Published: December 2022

Abstract
Coherent lines are generally more complex spatial curves, and the study of coherent lines is the basis for studying cutting trajectories of spatial coherent cutting machines. In this paper, the spatial geometry problem is transformed into an algebraic problem solving by establishing a mathematical model of spatial coherent line to find its parametric equations. Interpolation refers to the process of data densification. In this paper, a speed planning method that adapts to the curvature change of the Non-Uniform Rational B-Splines ( NURBS ) curve is proposed. After inputting the starting points and endpoints to the Computer Numerical Control (CNC), the computer will calculate the coordinate data of each step according to the characteristics of the line segment, carry out the speed planning and then complete the curve trajectory interpolation. The accuracy of the algorithm is verified by comparing the theoretical coherent trajectory and interpolated trajectory.
Missing Detection of The Clutch-Driven Disc Spring Assembly
Authors: Hou Daishuang , Gao Jingang 
Published: December 2022

Abstract
A detection system for the missing assembly of clutch-driven plate springs is established. The algorithms used in this system, such as point cloud data preprocessing, spring area positioning, and spring missing detection, are studied. Firstly, according to the characteristics of the clutch-driven plate spring point cloud, the Gaussian statistical method is used to eliminate the outliers incurred by system error and other reasons, and the two-sided filtering is performed on the clutch-driven plate spring point cloud that eliminates the outliers to eliminate the noise points with small ups and downs. Then, the theoretical division area is constructed by using the theoretical width between the clutch-driven plate springs and the theoretical width of the springs. Compared with actually recorded positions, the theoretical area is expanded so that the real spring point cloud data are in the corresponding positioning area; finally, the spring in the region is identified by using the characteristics of an inconsistent number of point clouds in different assembly conditions, so as to detect the missing assembly of the clutch-driven plate spring. The experimental results show that the detection accuracy of the clutch-driven plate spring assembly is as high as 100%. It can basically meet the detection requirements for the missing assembly of clutch-driven plate springs.
Research on Mobile Terminal Mobility Prediction Method Based on Unscented Kalman Filter
Authors: Zhang Jing 
Published: December 2022

Abstract
For mobile terminal users in the process of moving, due to the uncertainty of movement, how to effectively predict and reasonably allocate the Edge Servers (ESs) for mobile terminal users has become the key to solving the problem. Therefore, this paper proposes and designs a mobile terminal user mobility prediction method based on an Unscented Kalman Filter (UKF). According to the application scenario of Mobile Edge Computing (MEC), the edge server with computing resources is placed at the edge node of the network. The state equation and observation equation are constructed through the trajectory points of the mobile terminal users, and the trajectory prediction is completed using the UKF. By comparing the No Filter. Method, the Linear Kalman Filter. Method and the UKF method, the research results show that the proposed method can effectively reduce the error and improve the success rate of the task compared with the other two methods so that the prediction trajectory of mobile terminal users is more accurate and more applicable.
Vibration Analysis of the Non-abrasive Cryogenic Polishing Experimental Devices
Authors: Xu Anjun , Wang Yan , Qi Zhihui , Mu Guozhen , Lv Qiongying 
Published: December 2022

Abstract
Non-abrasive cryogenic polishing is a new method that can obtain ultra-smooth surfaces. For experimental devices, the vibration displacement, vibration frequency, and natural frequency can be obtained through model analysis under a 3D experimental model using ANSYS. Results show that the faster the ice wheel rotates, the smaller vibration of the experimental devices, and the higher the vibration frequency.
Grinding and Polishing Repair Technology and Experimental Research on Surface Defects of Flywheel Disc Semi-Finished Products
Authors: Shi Guangfeng , Mao Yuhang , Che Jianwei , Guan Yanji 
Published: December 2022

Abstract
The flywheel disc is an important engine component that is widely used in industries such as automobiles, ships, and flywheel energy storage. In this paper, single-factor experiment, and orthogonal experiment are used to explore the influence of abrasive particle size, grinding speed, grinding pressure, and grinding time on the surface roughness and material removal rate of flywheel disc semi-finished products (cold-rolled steel). The results show that the optimal combination of parameters for the surface defect repair process of flywheel disc semi-finished products is: abrasive particle size of W20, grinding speed of 40 r/min, grinding pressure of 3 psi, grinding time of 40 min, and an average surface roughness of 342nm. The repaired flywheel disc semi-finished product has great surface quality and meets the requirements of factory repair.
Research on Control Strategy of Buck Converter Based on Particle Swarm Optimization Fuzzy PID
Authors: Zou Jincheng , Xue Peng 
Published: December 2022

Abstract
Because buck converter is a typical non-minimum phase system, the traditional PID algorithm has the disadvantages of low control accuracy and high system overshoot, while fuzzy PID control only slightly improves the control effect. Therefore, this paper designs a control strategy based on particle swarm optimization fuzzy PID algorithm to enhance the control effect of the buck converter and combines chaotic variables to optimize the quality of the initial particle swarm. Finally, Matlab simulation experiments verify that the control strategy of fuzzy PID optimization using particle swarm optimization combined with chaotic variables has the advantages of short response time, high stability, and low system overshoot compared with the traditional PID algorithm and fuzzy PID algorithm.
Parameter Optimization of PID Controller Based on Improved Beetle Herd Algorithm
Authors: Li Jun , Chen Xingwu 
Published: December 2022

Abstract
The PID controller, although used in 95% of the loop operations in the automation field for practical control, still has a lot of shortcomings such as nonlinearity, hysteresis, and time-varying uncertainty, resulting in unsatisfactory control effects. To solve this problem, this paper proposes an improved beetle herd algorithm for PID parameter optimization. With the combination of the group collaborative optimization ability of particle swarm optimization, the global search and local search capability is strengthened through the test of the error-index ITAE and the optimized PID parameters. Finally, with the help of the PID controller simulation, the effectiveness of the algorithm is verified by comparing the effects of the four algorithms before and after the improvement.
Research Progress of Robot Vision Sensing Weld Seam Tracking Technology
Authors: Hu Zhiwei , Cheng Wei , Ge Hailong , Li Wenlong , Lu Tong 
Published: December 2022

Abstract
As the key technology of intelligent welding, seam tracking plays a vital role in the welding process. The development and application of visual sensing technology has laid the foundation for obtaining accurate weld position information. The intelligent combination of visual sensing and welding robots improves the stability and accuracy of welding seam tracking technology. This paper introduces the composition and principle of the welding seam tracking system, and the classification of visual sensing technology. This paper summarizes and analyses the welding seam image processing method and the research status of robot tracking control technology around the process of welding seam tracking. This paper summarizes the current problems of weld tracking technology and looks forward to the future development trend.
Signal generation and regulation of implantable nerve stimulator
Authors: Zhang Qinglei 
Published: December 2022

Abstract
In the treatment of nervous system diseases, implantable nerve stimulators have attracted more and more attention because of their obvious therapeutic efficacy and high safety. The generation and regulation of stimulus signals are the most important step in the design of an implantable nerve stimulator. The stimulation signals from the implanted nerve stimulator act directly on nerve cells. If the stimulus signal is not delivered accurately according to the set parameters, it will not only affect the therapeutic effect but also cause unpredictable malignant consequences. To generate stimulus signals that meet certain requirements, the different circuit structures need to be designed to be applied to the stimulators with different function types. In this paper, five types of stimulator circuits are introduced, and their strengths and weaknesses are analyzed based on the detailed introduction of the working principles of the different stimulator circuits, which might provide a theoretical and practical reference for future research.
Finger rehabilitation training and evaluation system based on EEG signals, machine learning and Fugl-Meyer scale
Authors: Liang Xiaohu , Zhao Qicheng , Liang Junming 
Published: December 2022

Abstract
For patients with digital hemiplegia caused by stroke, equipment such as mechanical exoskeleton devices are currently used to help recovery, but they are limited to many shortcomings of this method. This paper proposes to collect electroencephalogram(EEG) information through brain-computer interface (BCI) equipment. Combined with the research status of BCI system at home and abroad, we established the research idea of BCI system based on motor imagery by preprocessing the obtained information. According to the biological characteristics of human fingers and the needs of finger rehabilitation, a finger rehabilitation system was designed to assist hemiplegic patients in rehabilitation training. In the experiment, the EEG signals of several subjects in the two states of imagining finger movement and rest were collected through the EEG cap, and an appropriate feature extraction method was selected. Machine learning like logistic regression, random forest and deep learning were used for various classifications. The EEG feature vectors extracted by different subjects were classified and cross-validated. At the same time, the popular Fugl-Meyer scale was selected to quantitatively assess the patient’s limb function. The experimental results show that the comprehensive classification effect of deep learning is the best. The system performed well for the patient’s recovery process.
Mobile Robot Trajectory Estimation Algorithm Based on Adaptive EKF
Authors: Yi Chengqun , Wu Jiaye , Li Jiali 
Published: December 2022

Abstract
An adaptive control system based on extended Kalman filtering is designed for internal and external interference in real-world track-tracking tasks. First, the performance state of the wheeled robot at work is analyzed, and a kinetic model is developed. Then, the extended Kalman filter is used to achieve the real-time prediction of the external environmental disturbance amount, so as to obtain the error information that needs to be improved, and its error is eliminated. Finally, Lyapunov analysis is used to derive the stability of the improved rear wheel robot system and then confirm the feasibility of the scheme. The simulation verification analysis shows that the trajectory of the wheeled robot can be stably tracked steadily, which proves the feasibility and effectiveness of the proposed algorithm.
Research on Distribution Network Topology Identification Algorithm Based on Mutual Information Bayesian Network
Authors: Xia Zaiqi , Du Jun , Jiang Fan , Guo Yanpeng , Song Shaohua 
Published: December 2022

Abstract
In this paper, a distribution network topology identification algorithm based on mutual information Bayesian network is proposed. In this algorithm, the Bayesian model is mainly used to fit the nonlinear relationship among various variables such as photovoltaic, load, measured voltage, and distribution network topology. Then, the mutual information network is used to effectively divide the measurement continuous stage intervals of variables, thus improving the identification and analysis accuracy of the distribution network topology by Bayesian network, and solving the problems existing in traditional Bayesian network applications, such as difficult continuous data processing, poor adaptability of many continuous deformations, etc.
A Deployment Method for Unmanned Aerial Vehicles Based on Improved Neural Network
Authors: Yang Wenda , Wu Minggong , Wen Xiangxi , Zhang Zhe 
Published: December 2022

Abstract
The time for drones to complete their missions is limited. When sensors detect targets or perform multiple tasks, the pressure of insufficient resources can be quite high, and even task overload may lead to task failure. This paper focuses on a multi-UAV target assignment method. Compared with the classical model-solving method, which can find the satisfactory solution in a short time. Finally, through MATLAB simulation and verification, we find that the method in this paper has better dynamic adaptability to the complex and changeable environments.
Development and application of the multifunctional transmission roll-sliding friction tester
Authors: Shao Jiayin , Yi Lili , Han Wenhe 
Published: December 2022

Abstract
This paper aims to elaborate on the development and the main features of the multifunctional transmission roll-sliding friction tester. The tester adopts the independent drive for controlled relative movement, and the contacting specimen that sustains the radial loads can be replaced, so it can complete the rolling friction, sliding friction, and roll-sliding friction test. The integrated transmission performance test machine not only has solved the inconsistency between the friction and transmission experimental boundary conditions but also can precede the friction drive research. Piecewise calibration data and interpolating correction algorithm are used to avoid the affecting generated by the spindle friction to the specimen. The monitoring system software is developed by the LabVIEW platform, and the parameters are controlled automatically by the computer. Thus it can simulate actual working conditions very well and achieve automatic real-time data acquisition, processing and showing the results, etc.
Analysis and Experimental Research on Dynamic Characteristics of Horizontal Shaft System of Photoelectric Equipment
Authors: Liu Lei , Jiang WeiWei , He Bi 
Published: December 2022

Abstract
In order to study the transmission characteristics of vibration in the shafting of optoelectronic equipment, a horizontal shafting test platform for optoelectronic equipment is designed. Firstly, according to the special structure and load conditions of the three-row ball-column combined turntable bearing used in the horizontal shafting, a quasi-static model of the bearing load was established to solve the load distribution of the bearing and further calculate the bearing stiffness. At the same time, the bearing system was established. The dynamic model of the system is used to calculate the frequency response function of the system under the conditions of radial load and axial load and analyze the vibration transmission characteristics of the shaft system. Based on the finite element method, a finite element calculation model is established, the shafting dynamic model established is used to simplify the bearing, the modal parameters of the equipment are analyzed, and the experimental verification is carried out using the Siemens dynamic test system. The results show that the established model is effective and reliable. It provides a reference for studying the dynamic characteristics of the shaft system of optoelectronic equipment.