bluuebunny/crossref_metadata_2025_split huggingface dataset:
LSTM-CNN network for human activity recognition using WiFi CSI data
Authors: Shang Shunuo , Luo Qingyao , Zhao Jinjin , Xue Ran , Sun Weihao , Bao Nan 
Published: April 2021

Abstract
Human Activity Recognition (HAR) has had a diverse range of applications in various fields such as health, security and smart homes. Among different approaches of HAR, WiFi-based solutions are getting popular since it solves the problem of deployment cost, privacy concerns and restriction of the applicable environment. In this paper, we propose a WiFi-based human activity recognition system that can identify different activities via the channel state information from WiFi devices. A special deep learning framework, Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN), is designed for accurate recognition. LSTM-CNN is going to be compared with the LSTM network and the experimental results demonstrate that LSTM-CNN outperforms existing models and has an average accuracy of 94.14% in multi-activity classification.
Design of Intelligent Safety Protection Robot Based on Global Position System and Machine Vision
Authors: Ming Yang , Yufei Li 
Published: April 2021

Abstract
In this paper, an intelligent safety protection robot based on the integration of Global Position System(GPS) and machine vision is designed. The robot takes STM32F407 as the control core and is equipped with a variety of environmental monitoring sensors to realize real-time monitoring of the surrounding environment and alarm for potential safety hazards. In order to realize the stable and accurate autonomous navigation of robot, a system combining GPS technology with visual simultaneous localization and mapping (V-SLAM) technology is designed. GPS module collects longitude and latitude information, driving speed and heading Angle to complete the absolute positioning of the robot. Machine vision device collects image information, and the relative positioning of the robot is completed through digital image processing technology. The two positioning information was fused and output new positions and postures through Unscented Kalman Filter (UKF). Through the experimental verification of the combined navigation and positioning effect, the GPS and machine vision integrated navigation device has high precision, and the maximum error is controlled within 0.1 meters.
Research on the Reform of Investigation Methods Guided by Dynamic Data Forecast
Authors: Tang Liangyan 
Published: April 2021

Abstract
This article analyzes the constituent elements of dynamic data forecasting and guiding investigation. The research content of this article includes technical elements, resource elements, thinking elements, etc. The author combined with dynamic data to predict the attributes of guiding investigations, and studied content including dynamics, openness, diversity, and integrity. This paper studies the spatial analysis method, detection analysis method, matrix analysis method, predictive analysis method, risk assessment analysis method, node analysis method and so on. The purpose of this article is to guide the reform of investigation methods, speed up the development of investigation work, and improve the practicability of investigation results.
Design of Face Recognition Access Entrance Guard System with Mask Based on Embedded Development
Authors: Ruiqin Lin , Wenan Tan , Zhenyu Chen , Qinqin  
Published: April 2021

Abstract
This paper investigates all kinds of access entrance guard control systems at home and abroad and analyzes their advantages and disadvantages. COVID-19 epidemic has a serious impact on life, travel must wear a mask, so that the access entrance guard control system can not carry out face recognition under the mask. In view of this kind of situation, an embedded face recognition access entrance guard control system with mask based on EAIDK-310 development board is designed. The system can complete face recognition and body temperature measurement without contact, and drive the motor to open the gate. After testing, the system is suitable for deployment in companies, communities, campuses and other small application scenarios. It is convenient to travel and can reduce the impact of the epidemic.
Bibliometric research in the field of artificial intelligence
Authors: Tu Wenyan , Fang Ji , Fangyu  , Jiao  , Ci Yutong 
Published: April 2021

Abstract
This paper analyzes the development trend of global artificial intelligence from the perspective of bibliometrics. From the publishing trend, the number of papers published in the field of artificial intelligence is growing rapidly. China and the United States are among the top countries in the output of scientific research papers, and India has the fastest cumulative growth rate. In the research direction, the research on computer vision, image, deep learning and neural network is the research hotspot in recent years.
Application Research of Automatic Garbage Sorting Based on TensorFlow and OpenCV
Authors: Hu Jing , Zhang Bo 
Published: April 2021

Abstract
Relying on manual garbage classification, the classification efficiency is low, and because of the classification environment is bad, the classification task is heavy, it is very adverse to the health of the classification personnel. With the development of artificial intelligence, artificial intelligence technology has advanced by leaps and bounds. After the concept of deep learning was proposed, the development of artificial intelligence was driven to practical application. And the advantages of deep learning are obvious, which also makes automatic garbage sorting possible. With the development of deep learning, a large number of deep learning network framework structures have gradually emerged, and a group of open source frameworks represented by TensorFlow and Keras have been widely applied. This paper proposes an application research on automatic garbage sorting based on TensorFlow and OpenCV, an open source image library, in order to realize automatic garbage recycling.
Research on intelligent perception and human activity monitoring for people with inconvenient movement
Authors: Zhang Tianping , Tang Xiaoping , Li Lijie 
Published: April 2021

Abstract
Aiming at the problems of various sensors, complex recognition algorithm poor implement ability and real-time performance in current human activity state recognition methods, a human activity monitor based on single three-axis acceleration sensor is designed. By collecting acceleration data of human waist, using sliding time window method to extract time domain features, four active states are identified: long-term violent active state. Long-term static state, fall state and normal active state. The technical development and the existing difficulties and problems are discussed for future related research.
Deep research on big data index analysis method in intelligent manufacturing industry
Authors: Song YuXiang 
Published: April 2021

Abstract
Big data analysis is widely used in intelligent manufacturing industry. Data analysis refers to analyzing a large amount of data collected by appropriate statistical and analytical methods, summarizing and understanding them, and digesting them, so as to maximize the development of data functions, give full play to the role of data, and improve and strengthen the intelligent level of manufacturing system. Data analysis is to extract useful information and form conclusions, and to study and summarize the data in detail. The data of intelligent manufacturing system is also called observation value, which is the result of experiment, measurement, observation and investigation. The data processed in data analysis is divided into qualitative data and quantitative data. The results of data analysis are of great significance in the intelligent manufacturing industry.
Real-time workshop digital twin scheduling platform for discrete manufacturing
Authors: Zhifeng LIU , Yueze ZHANG , Caixia ZHANG , Jun YAN , Shiyao GUO 
Published: April 2021

Abstract
Compared with other production methods, multi-variety, small-batch production driven by order become a lot more sensitive to the disturbances of workshop environment, orders, and processing equipment. This makes a great impact on workshop scheduling. Aiming at this problem, this paper designs a real-time workshop digital twin scheduling platform for discrete manufacturing. It improves the flexibility of the intelligent workshop and the response processing speed after dynamic disturbance. The platform can real-time monitor of the physical workshop and track orders, products, equipment and other information. Further, the platform and visualization technology were explored to work together. Then, the true display of changes after production line decision was displayed. It enables managers to carry out production scheduling verification in the virtual workshop, which reduces the repeated changes of physical workshop production scheduling. Finally, the platform was verified in a discrete manufacturing workshop. The scheduling platform based on digital twins helps manager to immersivity develop factory production strategies. The production efficiency was then enhanced. The platform can ensure the effective operation of the manufacturing system.
Applications and Prospects of Mems Sensors in Automotive
Authors: Jin Li 
Published: April 2021

Abstract
MEMS sensor is a new type of sensor and is made by micro-electronic and micro-mechanical processing technology. It has many advantages such as small volume, light weight, low cost, low power consumption, high reliability, suitable for mass production, easy integration and intelligent realization. It is widely used in the automobile, effectively improving the performance of the automobile sensor, promoting the progress of the automobile industry and the intelligent automobile. This paper mainly discusses the market size of MEMS sensors and their applications in the automotive field, focusing on MEMS pressure sensors, MEMS acceleration sensors and gyroscope sensors. The development direction of MEMS sensors in the automotive field is forecasted.
Digital twin-based smart manufacturing cell: Application Case, System Architecture and Implementation
Authors: Zhang Jiyuan , Li Pengzhong , Luo Liang 
Published: April 2021

Abstract
Smart manufacturing is considered to be a universal solution for upgrading manufacturing. Currently, the manufacturing tasks are becoming more personalized and the complexity of the manufacturing environment is increasing. Therefore, the manufacturing system needs to have a high level of learning and cognitive abilities. In order to cope with changes in the manufacturing environment, this paper proposes a system architecture of a smart manufacturing cell, which can intelligently sense, analyze, and make decisions to support autonomous manufacturing. Through the implementation in the experiment, it is verified that the proposed architecture is reasonable.
An adaptive slicing approach for processing STL massive data model in batches based on layer merging
Authors: Shao Minghao , Wei Chao , Cui Bin , Li Yongkang , Zheng Tengfei 
Published: April 2021

Abstract
Slicing is one of the core parts of the additive manufacturing software system, which completes the function of transforming the 3D model into a 2D profile. The adaptive slicing algorithm uses different layer thicknesses for layering in different areas according to the changes in the geometry of the mesh model. Where the model is more complex and the curvature changes a lot, a smaller layer thickness is used to approximate the model. In areas of large curvature of the model, maximum layer thickness is used to improve printing efficiency. With the development of additive manufacturing technology, grid model files such as STL have become larger and larger, and the amount of data needed to be processed by slicing software has increased dramatically. Existing slicing software is limited by computer hardware and cannot process massive data model. It greatly limits the development of additive manufacturing technology, so it is urgent to propose a new method to solve the rapid stratification of mass data model. In this paper, we proposed an adaptive slicing approach for processing STL massive data model in batches based on layer merging. At the same time, it is compared with the fixed-layer thickness slicing method, which shows that the algorithm can improve printing efficiency under the premise of ensuring accuracy.
The Software Design of Intelligent Campus Safety Cabinet under Epidemic Situation
Authors: Zhaofan Zhou , Lingying Tu 
Published: April 2021

Abstract
During the outbreak and future public health security, the safety cabinet industry gradually took to the forward momentum of development, the safe cabinet from the normal delivery tank through the software design to implement the "sell" face-to-face in universities. According to the survey, most students lose some take-out. Safety cabinets not only solve the problem of the safety delivery courier, also pay attention to public health in this era of successful implementation without personnel contact. Through the software design, the dining room also unified blocks with the school management, and students can order food through the canteen they want to go to, which provides a large number of different choices for students so that they won't get tired of eating in the same area. With the popularization of 5G in the future, the combination of "unmanned delivery mode" can reduce more risks in terms of public health and make people's lives more convenient.
Intelligent detection device of pavement disease based on image recognition technology
Authors: Guo Wentong 
Published: April 2021

Abstract
In recent years, the continuous progress and development of artificial intelligence technology, especially the technology represented by deep learning and image recognition, have made great breakthroughs, and put forward new methods for road surface disease detection. In this paper, image recognition technology is applied to the direction of high-level pavement detection, and an intelligent disease detection robot is developed based on GPS navigation technology, which realizes the integration process of pavement disease from detection to location.
On-line monitoring of penetration state in laser-arc hybrid welding based on keyhole and arc features
Authors: Zhang Minghai , Shu Leshi , Zhou Qi , Jiang Ping , Gong Zhaoliang 
Published: April 2021

Abstract
Incomplete penetration is a typical defect in laser-arc hybrid welding. On-line monitoring of welding process is an important method to assess welding quality. In laser-arc hybrid welding, there is a strong correlation between keyhole, arc and incomplete penetration. Therefore, an on-line monitoring method of penetration state based on keyhole and arc features is proposed in this paper. In the proposed method, the images of keyhole and arc in laser-arc hybrid welding are captured by high-speed camera, and then the keyhole and arc features are extracted by image processing algorithm. Finally, the features are used as input to classify the penetration state using SVM model. The results show that the SVM model based on keyhole and arc features can accurately identify the penetration state.
Trajectory tracking control method of robotic intra-oral treatment
Authors: Cheng Qiang , Xu Wenxiang , Wang Yi , Liu Zhifeng , Hao Xiaolong 
Published: April 2021

Abstract
At present, people suffer from a high rate of cross-infection of oral diseases, and it is an urgent clinical need to explore effective methods to promote high-security and high-quality imaging. This paper proposes a collaborative robot control strategy that assists in oral diagnosis and treatment. This method can track the dynamic movement of the patient's upper and lower jaw during treatment. According to the small space of the oral cavity and the change of the tooth position, dynamic trajectory tracking with adaptive control is performed on the robotic arm. This control strategy is of great significance for accurate oral diagnosis and treatment and reducing cross-infection between doctors and patients.
Algorithm for detecting brightness differences in noisy images based on the Wilcoxon criterion
Authors: Dudka N , Fedorov E , Ferenets A 
Published: April 2021

Abstract
To detect brightness differences in grayscale images, in previous works it was proposed to use the nonparametric Wilcoxon criterion. At the same time, the obtained research results showed a sufficient effectiveness of the application of the criterion for highlighting the brightness differences in images with noise without preliminary filtering. The application of the criterion involves the transformation of the image into such an attribute as the value of the rank function for each pixel of the analyzed image area. Calculation of the extremum of the rank function makes it possible to establish the location and type of brightness differences in the image. However, as studies have shown, the value of the extremum value depends on the signal-to-noise ratio in the image and, along with the true extrema, local extrema are also distinguished, which complicates the solution of the problem of further image segmentation. This paper presents the results of statistical studies on the use of the Wilcoxon test for detecting brightness differences in images with different signal-to-noise ratios and sample sizes. The minimum signal-to-noise ratio at which the extremum of the rank function tends to its maximum or minimum value has been established. Also, based on the statistical analysis of the behavior of the rank function to exclude the allocation of local extrema, it is proposed to use the difference of the rank functions for the analyzed rows and columns of the processed image
Simulation Complex for Debugging of Control Algorithms of the Test Bench
Authors: Shmidt I A , Ivanov P V , Gribkov I N 
Published: April 2021

Abstract
The object of research and development is an air heating and delivery automatic control system of the test bench for testing of gas turbine engines. It is based on a test bench equipped with a gas turbine engine, a long air duct with dampers regulating the airflow, and the tested mechanism. It must maintain the required airflow characteristics and the air charge motor’s operating mode line. To debug the algorithms of the object of research, a simulation complex was developed, which can reproduce all the features of the test bench’s behavior. The combination of the automatic control system and a simulation complex is a semi-natural model. Purpose is to develop a simulation complex for the debugging of the control algorithms and a mathematical model of the stand and the engine under test. As result, a simulation model based on the implementation of VeriStand technology was created. The program provides a uniform way to access heterogeneous models executed in Simulink. These models display different ways of describing the processes and features of the behavior of the modelled object. The simulation results can be compared to the behavior of a real system, which allows to debug the algorithms of the automatic control system. The developed simulation complex is currently used by specialists to make the mathematical models of the test bench components and the tested product more precise, as well as to debug the control algorithms.
Application of the “Bow-Tie” method to assess the risk of incapacitation of the sucker rod pump
Authors: Bochkarev S , Leyzgold K , Shilova S 
Published: April 2021

Abstract
The article presents one of the methods for assessing the risk of electrical equipment accidents at an oil and gas production and transportation enterprise, in order to improve the smooth operation and efficiency of the use of electrical and technological equipment of oil fields. As an example, the operation of a rod pump is considered.. The concept of a systematic approach for risk analysis at industrial enterprises is proposed.
Virtual Enterprise Approach for teaching students in electrical engineering
Authors: Shaykhutdinov D , Krivtsun A , Gaaber J 
Published: April 2021

Abstract
This article deals with the original approach which is proposed - a “virtual enterprise” that differs from the well-known by a more in-depth focus on the future specialist’s adaptation to the market economy. The methodology of a virtual enterprise is based on a project-oriented approach. The tools for the implementation of information exchange within the educational virtual enterprise, as well as for the implementation of the process of product design and testing has been proposed and considered. To implement the information exchange environment the usage of the training version of the SAP ERP application package has been proposed. To implement the environment for the development and implementation of technical solutions the usage of hardware and software of National Instruments has been proposed for realization of a concept.
New Periodic Table of Elements: Electron Configuration and Motion, and Formation of Simple Compound
Authors: Peng Y B , Lei T , Zhen H T , Yuan Z X , Xu H , Wen F 
Published: April 2021

Abstract
Based on the number of protons and electrons in the existing element, this paper believes that the electron configuration of the element needs to be changed in order to obtain its new properties and principle of electron pairing. The new electron configuration is the square of the number of periods. The first, second, third, and fourth periods contain 1, 4, 9, and 16 electrons respectively. Atoms evolve by the movement of electrons from the outer core, attracting electrons from different atoms to form compounds. When low hierarchy elements combine with high hierarchy ones, their electrons preferentially choose electrons of higher period of each other for coordination. So H atomic electrons are more likely to attract and pair with electrons of the second period of C, N and O to form bonds, while the outermost electron of O in the third period tends to pair with electrons in the fourth period of P, S and Cl. Then the special structure of ammonia and water molecules can be deduced, and the double bond characteristics of highpriced acids of P, S and Cl can also be explained. New periodic table of elements makes it easy and convenient to explain chemical phenomena and facilitate the understanding of the micro world.
Structural and Electronic Study of Palladium(II) Complexes by a Theoretical Approach
Authors: Saadiah Abdullah Nur Halimatus , Nazirah Ozair Lailatun , Muhammad Anas Muhammad Mus’ab Anas , Mohd Yamin Bohari 
Published: April 2021

Abstract
The established method of synthesising tetraaza macrocyclic ligand by introducing a transition metal ion as a templating agent has demonstrated difficulties in the decomplexation process. Therefore, this study examined the potential of forming the ligand before converting them into transition metal complex and further explored the characteristic of Pd2+ tetraaza macrocyclic complex through density functional theory (DFT) calculation. The results show that the cation successfully fits in the macrocyclic ligand as a result of the electron transfer process.