bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Network Information Management System Based on C/S Architecture
Authors: Wang Ruibin
Published: September 2021

Due to the incomplete data preservation of traditional systems, the success rate of network information data update is reduced. Based on C/S architecture, a network information management system is designed. In terms of hardware design, the C/S architecture allows for the optimisation of the RFID circuitry to speed up the rapid conversion of data. In software design, information management model is established based on C/S architecture, protocol identification method deletes abnormal data in the transmission process, fuzzy method sets up data storage mode, centralizes control of network information, and completes the design of network information management system. The experimental results show that the new system has an average success rate of 98.96%, which is 9.16% and 10.46% higher than the traditional system, respectively, and can increase the update effect of network information.
Proximal Policy Optimization with Future rewards
Authors: Yu Chengcheng , Zhang Lijun , Yin Dawei , Peng Dezhong , Huang Haixiao
Published: September 2021

Among the current reinforcement learning algorithms, the Policy Gradient algorithm (PG)[7] is one of the traditional and most widely used algorithms, but it has the disadvantage of unstable gradient estimation, and the newly Proximal Policy Optimization algorithm (PPO) [8]solves the problem. It solves the stability problem, but the update policy is slow, and it is easy to produce over-fitting when the training times are too many. In this article, a new method is proposed, referring to Asynchronous Advantage Actor-Critic (A3C)[9], the basic PPO algorithm is trained in parallel, and a method that considers future rewards is introduced, and the future rewards are also calculated to the current. In the reward, through the OPEN GYM platform and the experimental results of capturing at any position of the robotic arm, our actions can ensure a faster training speed, while also avoiding overfitting during long-term training.
Computational simulation and theoretical comparative study for the complexes of heme-iron and heme-zinc
Authors: Wang Yashi , Lei Zhiming , Lan Wenbo , Wang Xiaofeng , Li Qianru , Zeng Huiwen , Meng Yanbin
Published: September 2021

By using computer technology, molecular simulation and analysis of the coordination structure of heme iron and complex formed by the heme ligand and Zn are carried out under the same level of calculation. Studies have found that the ability of heme ligands to capture Fe is significantly stronger than that of Zn. However, the binding energy and the stability of the complex of heme ligand and Zn are stronger than those of the complex of heme ligand and Fe, and at the same concentration, the complex absorbs light in the near-ultraviolet region to a greater degree.
The security function dynamic calling scheme for software-defined security
Authors: Ma Yuanyuan , Guo Zhimin , Yang Wen
Published: September 2021

With the rapid development of cloud computing, various network attack methods are becoming more advanced, and the attack speed is getting faster. Traditional security protection solutions can no longer adapt to new network attacks, bringing significant challenges to security protection in virtualized network environments such as cloud computing. Based on these problems, this paper proposes a dynamic calling mechanism of security functions for software-defined security based on software-defined network technology. This mechanism defined the strategies of dynamically scheduling of virtual security service nodes in the virtualized network environment. The strategies describe the network’s data flow and virtual security devices by extending the attribute-based access control policy model. It can dynamically construct the mapping relationship between network flow and virtual security devices according to users’ security requirements, thus forming a personalized security service chain for specific network flows. This mechanism can protect the “north-south” network flow at the IoT edge agent according to the user security business requirements.
Design of system-level hot standby redundancy-based signal system
Authors: Zhang Yu , Wang Xiaoyong , Yu Yi , Chu Pengzi , Xu Ye
Published: September 2021

Focusing on the improvement of the availability for signal systems, a system-level heterogeneous hot standby redundancy-based signal system is discussed. The system includes a communication-based train control system (CBTC), a track circuit-based train control system (TBTC), and a switching unit. The CBTC and TBTC are respectively connected to the communication system via the switching unit. Under normal condition, the CBTC is connected to the communication system via the switching unit, and the function commands received by the train come from the CBTC. When the CBTC fails, the TBTC is connected to the communication system via the switching unit, and the function commands received by the train come from the TBTC. The switch between the CBTC and the TBTC is automatically executed by the system. Simulation results showed that the proposed design in this paper improved the availability of the signal system and reduced the impact of failures on operations.
Analysis of Lower Limb Muscle Fatigue Based on Surface Electromyographic Signal
Authors: Huang Shuping , Jang Haiyan , Chen Yan , Shi Shaoyun
Published: September 2021

Surface electromyographic (sEMG) signal contains abundant information such as joint torque and joint motion, which is widely used in human-computer interactive intelligent rehabilitation equipment. In this work, the ankle torque of lower limb is taken as the research object, and the feature parameters of sEMG which represent the fatigue state are analysed. Advance prediction of fatigue features for specific time periods was performed using a normalized minimum average square (NLMS) filter. While the modified cerebellar model neural network (WFCMNN) is used to classify fatigue, which can be divided into three states, namely no fatigue, transition to fatigue, and fatigue. The results show that the accuracy of classification is 96.429%, which is better than other advanced models. At the same time, sEMG signal is used to predict fatigue in advance, which can solve the problem of differences between different individuals. Such strategy is helpful for doctors and physiotherapists to carry out rehabilitation treatment for patients, as a pre judgment and diagnosis index.
l-extra edge connectivity of graphs
Authors: Li Yalan , Zhang Shumin , Ye Chengfu
Published: September 2021

When we design an multiprocessor systems of interconnection network, one important question is considering the reliability evaluation of network. For a positive integer l, the l‐extra edge connectivity λl(G) of a connected graph G, is the minimum number of edges so that when removal the edges from G, then we get a disconnected graph and each component has more than l vertices. In this paper, we get the exact values of l‐extra edge connectivity. Upper and lower bounds of l‐extra edge connectivity. Get the extremal results of this connectivity.
Software defect prediction based on CS-BP neural network
Authors: Ma Jiawang
Published: September 2021

Software defect prediction can detect whether there are defects in the program module so as to effectively reduce the unnecessary cost of software development and maintenance. In this paper, the limitation of the traditional BP neural network in the field of defect prediction leads to the inaccuracy of the prediction results. By using the global optimization ability of cuckoo search, the BP neural network is improved, the important initial parameters of the network are optimized, and the software defect prediction method of CS-BP is proposed. The experimental results show that compared with traditional machine learning algorithms such as BP neural network, J48 and SVM, CS-BP method has a better effect on the prediction of software defects.
Massive MIMO Channel Estimation Based on Compressed Sensing
Authors: Bai Xiaojuan , Guan Lu , Zhao Chao , Dao Wei
Published: September 2021

Obtaining accurate channel state information (CSI) is an important prerequisite for achieving good performance of the Massive MIMO system. The traditional pilot-based channel estimation algorithm has low spectrum utilization. The channel estimation algorithm based on compressed sensing can make full use of the sparsity of the channel and realize channel estimation with fewer pilots. In this paper, wavelet denoising is combined with a sparse channel estimation algorithm based on Orthogonal Matching Pursuit (OMP), and Cramer-Rao Lower Bound (CRLB) is derived. The simulation results show that this method has better performance.
Numerical Investigation of Aeroelastic Deformation Effect on the NASA Common Research Model
Authors: Zhang Lu , Xiao Zhongyun , Ma Shuai , Liu Fan
Published: September 2021

The risk of the aeroelastic deformation of the wings to the flight safety has become increasingly prominent for commercial transport aircraft due to the requirements for lightweight structure. In this work, Reynolds averaged Navier-Stokes (RANS) method coupled with transfinite interpolation were employed to investigate the influence of static elastic deformation of wing on aerodynamic characteristics of NASA CRM. Both bend and twist distributions were scaled in numerical simulations based on dynamic pressure, which was shown to be reasonable by the compassions between the calculations and measurements. The numerical results show premature flow separation in the middle and outboard of the wing for original configuration. Furthermore, the flow separation was supressed by the upward bending of the wing and negative twist in the leading edge, and the aerodynamic characteristics of the aircraft were improved by the aeroelastic deformation.
Network security prediction method based on kubernetes
Authors: Ruan Zhengping
Published: September 2021

In order to improve the stability and security of network operation, a network security prediction method based on kubernetes is proposed. CPU resources are managed by kubernetes. Based on this, terminal data and resources are converged, and network extension is standardized according to the final situation value. Combined with POS algorithm, starting from the group theory, through the cooperation and competition between different particles in the network, a particle swarm optimization model of “network running speed network communication” is established. Through the relationship of particle swarm optimization in the network, the SVR parameters are optimized. The network security is predicted by extracting the characteristics of network load. Through the application of the design method, it is proved that this method can realize the effective prediction of network operation security.
Simulation and Research of DME Signal Coverage
Authors: Zhang Xianhao , Zhuang Gangqiang , Guo Kang , Luo Zhongmei
Published: September 2021

In civil aviation land-based navigation equipment, the DME(Distance Measuring Equipment) system is a widely used short-range navigation equipment. Through the research on the antenna of the DME equipment, the antenna signal of the DME equipment is modeled and simulated, and the electromagnetic signal three-dimensional pattern of the DME equipment and the corresponding pattern of the E plane are obtained. On the basis of mastering the antenna signal radiation characteristics of each navigation device, the DME coverage area is simulated and analyzed.
Ultra-short-term Wind Power Output Prediction Based On LS-WMC Combined Model
Authors: Du Yanan , Pang Zhengning , Qi Jingxian
Published: September 2021

In this paper, an ultra short term wind power output prediction method based on least square and weighted Markov chain model is proposed. Firstly, the wind farm output is fitted based on the least square method, and then the prediction accuracy is improved by using the weighted Markov chain model. At the same time, the partial exponential weighting method is used to improve the prediction accuracy of ultra short-term wind power output on the basis of reducing the generation frequency of transition probability matrix, so as to optimize and improve the prediction results. The results show that the method can improve the prediction accuracy.
Latent Fine-grained Features embedding model for Unsupervised Zero-shot Learning
Authors: Tian Guiyu , Tao YiZheng , Xie Yang
Published: September 2021

Zero-shot learning (ZSL) aims to identify image categories that never appear in the training set by learning a mapping from visual information to the semantic space. For existing works in recent years, it has been paying much attention to user-defined-attributes-based supervised ZSL models and manual annotation-based unsupervised ZSL methods, whilst the important drawback of user-defined attributes is ignored. User-defined attributes usually need to be precisely annotated not only for seen classes but also for unseen classes. This procedure of collecting user-defined attributes is an error-prone and time-consuming work limiting the scalability of the methods to a great extent. Moreover, user-defined attributes are semantic embedding but they are not exhaustive. In this paper, we propose a manual annotation-free unsupervised ZSL method with a great scalability which is a benefit for the large-scale ZSL tasks, just using public word vectors of categories without any dedicated attributes annotation efforts. In addition, our approach can automatically extract latent fine-grained features to reduce visual information losses caused by the absence of user-defined attributes. Extensive experimental results show that our method outperforms the previous methods among the manual annotation-free unsupervised ZSL methods.
Research on phase diagram of traffic flow in a single loop roundabout under open boundary condition
Authors: Xue Wandong , Zhang XiaoDan , Jia JinFang , Zhao Yu
Published: September 2021

The cellular automation traffic flow model of roundabout with inner-roundabout-lane, injection-roundabout-lane and extraction-roundabout-lane is used to study the traffic flow of single loop roundabout under open boundary conditions. Through computer simulation, the relationships between the entrance probability, exit probability, vehicle braking probability and system flow, the average speed of each lane and system in the open boundary conditions are studied.Besides, the space-time diagram of vehicles on the injection-roundabout-lane with different entrance exit probabilities and the system phase diagram are established. In the system phase diagram, the critical entry probability and exit probability values of each part of the phase diagram under different braking probability are given. The results show that the system traffic flow can be divided into three phases: the phase in which the system flow changes with the entrance probability, the phase in which the system flow changes with the exit probability, and the phase in which the system flow has nothing to do with the entrance probability and exit probability. This will provide some guidance for road management.
Li-ion battery state of health Prediction based on Long Short-Term Memory Recurrent Neural Network
Authors: Lin Jingdong , Yan Guansong , Wang Chang
Published: September 2021

The state of health (SOH) prediction of lithium-ion battery is essential for the health management of batteries. At present, the prediction method combined with the extraction of health indicators in charge-discharge process has received extensive attention, however, many studies ignored that the extraction of battery discharge data will be affected by the actual operating conditions, which will affect the effectiveness of health indicators extraction. In this work, a type of recurrent neural network (RNN), which is long short-term memory-RNN(LSTM-RNN), is proposed to prediction the SOH of Li-ion batteries through the data of charging process and capacity. Because the different choice of network parameters will also affect the performance of the model, particle swarm optimization (PSO) algorithm is used to optimize LSTM model. The test results show that this method can effectively predict SOH of battery, and the maximum RMSE is less than 0.01. Compared with the traditional LSTM algorithm, it has higher accuracy.
Image Compressed Sensing and Reconstruction of Multi-Scale Residual Network Combined with Channel Attention Mechanism
Authors: Zeng Chunyan , Wang Zhenghui , Wang Zhifeng , Yan Kang , Yu Yan
Published: September 2021

Most of the existing compressed sensing reconstruction algorithms based on deep learning only use simple stacked convolutional layers to extract image feature information, which cannot extract sufficient image information; and each feature maps are treated equally in the reconstruction process, which lacks the ability of discriminative learning across feature channels and can’t make full use of the representation capabilities of convolutional neural network. This paper proposes a new multi-scale image compressed sensing reconstruction network based on residual network and channel attention mechanism. We use the residual network to increase the network depth, which reduces the information loss in the convolutional process through the skip connections in the residual block. It can obtain richer image information and protect the integrity of data information. We also add channel attention mechanism to adaptively scale each feature maps to enhance effective feature information and suppress invalid feature information. The experimental results show that the performance of image reconstruction is greatly ameliorated compared with the existing the state-of-the-art methods.
Inverse dynamics modeling of robots based on sparse spectral gaussian process regression
Authors: Huang Cuiyi , Wang Yang
Published: September 2021

In robot control systems, inverse dynamics calculation of the robotic arm is essential. In this paper, we propose a different inverse dynamics modeling method—sparse spectral Gaussian process regression (SSGPR). Since using Gaussian process regression for robot inverse dynamics modeling is computationally intensive, to address this drawback, it is proposed to apply sparse spectral Gaussian process regression on robot inverse dynamics modeling, the core of which is the sparsification of the GP’s spectrum for the purpose of improving computational efficiency. Experiments show that sparse spectral Gaussian process regression can improve the computational efficiency and outperform other regression methods while ensuring the computational accuracy.
An image processing toolbox based on MATLAB GUI
Authors: Deng Qianyu , Chen Xu
Published: September 2021

Our research realizes the basic processing of images based on MATLAB GUI. The functions include image reading, storage, display, adding noise, denoising, image enhancement, edge detection, image segmentation, discrete Fourier transform, wavelet transform, feature extraction, target recognition, color image processing, etc. At the same time, the image can be stylized and different filter processing can be carried out on the image.
Research on Facial Expression Recognition Based on Improved Deep Residual Network Model
Authors: Chen Ji , Luo Xiaoshu , Meng Zhiming , Li Wanting
Published: September 2021

Facial expressions are the main external manifestations of human emotions. Facial expression recognition technology can be used in medical, investigation, education and other application scenarios. Aiming at the disadvantages of slow convergence speed and low recognition accuracy of traditional neural networks, in order to optimize the network more efficiently and improve the recognition rate of facial expressions, a facial expression recognition method based on improved convolutional neural networks is proposed.First, the deep residual network ResNet18 is improved, and then the improved ResNet18 network is used to extract global expression features of face images, and then the self-attention weighting module is introduced to calculate the expression features of each face image and output one The corresponding weights are used to weight the loss function. Finally, the two public expression data sets of CK+ and RAF-DB are used to experimentally verify the method in the article. The accuracy of facial expression recognition reaches 98.89% and respectively. 87.13%, compared with the original deep residual network ResNet18 model and other types of network models, the facial expression recognition rate has been significantly improved, which proves that this method can effectively improve the accuracy of facial expression recognition and has certain application value.
Land classification based on high resolution remote sensing images
Authors: Su Ziyang , Zhong Yuanchang
Published: September 2021

Land information is an important information related to the timely adjustment of land management policy, which can significantly improve the efficiency of land management. The traditional land information collection completely depends on field survey of grass-roots personnel, which is not only time-consuming and laborious but also can not guarantee the accuracy of information. With the rapid development of remote sensing technology, using remote sensing image to obtain land information is an important means to conduct land investigation and detect whether crop planting area is up to the standard. At present, the method of artificial neural network (ANN) learning classification has achieved great success in the land classification, but there is still room for improvement in the classification accuracy. In this paper, a new Algorithm is introduced-shuffled frog leaping algorithm (SFLA), the important parameters of ANN are optimized. The traditional traversal method is improved to a combination of global optimization and local optimization, which can effectively reduce the search time, increase the generalization ability of the model and improve the classification accuracy. Through the experiment of remote sensing data of Fengqi town, Luochuan county, Yan’an city, Shaanxi province, it is shown that SFLA can effectively increase the accuracy of ANN in land information classification. It has achieved the paper research goal.
Research on Ultrasonic Localization Method of Moving Objects Based on Improved TOA Algorithm
Authors: Zhang Xinghong , Chen Ran , Xu Yi , Sun Bingman , Zeng Fanfeng
Published: September 2021

In the process of ultrasonic positioning of moving objects, a position algorithm TOA is optimized and improved due to the problem of delay caused by sequential ranging of the sequential ranging of the ultrasonic transmitter and receiver, the system’s solving time, and the signal transmission time. By setting an error compensation factor for the velocity of the object to be located and the unit positioning time of the system, the error is compensated to achieve the same positioning accuracy when the object to be located is stationary. The simulation results show that the positioning accuracy can be stabilized within 3 cm at a certain speed, and the positioning can be performed well for objects to be positioned with a certain speed.
A passive DDoS attack detection approach based on abnormal analysis in SDN environment
Authors: Sun Shimin , Zhang Xinchao , Huang Wentian , Xu Aixin , Wang Xiaofan , Han Li
Published: September 2021

Most of the detection methods against DDoS attacks are based on periodic detection, which leads to high communication overhead, untimely detection, and slow attack response. This paper proposes a passive abnormality detection approach. First, we record the two flow-table characteristics of the regular switches. Then, based on dynamic threshold method and Grubbs outlier test method, we make a determination of abnormal switches. This method reduces the amount of data duplication and regular traffic collection. Moreover, we use Support Vector Machine (SVM) algorithm to evaluate the performance of the passive anomaly detection method. The experiment results show a better performance than active period DDoS attack detection approaches.
Color speckle measurement in laser display
Authors: Shu Wei , Liu Hong
Published: September 2021

In recent years, with the continuous development of laser projection display technology, people’s choice of electronic display equipment has become more diversified.However, due to the high coherence of the laser used for imaging in the laser projection display device, the speckle phenomenon is more obvious than other display devices, which will greatly affect the user’s actual perception. A color speckle measurement device based on XYZ filter is designed. The computer software is used to control the camera to take speckle pictures under different filters, and calculate the speckle contrast of red, green, blue and white fields. A color speckle measurement device based on XYZ filter is designed. The computer software is used to control the camera to take speckle pictures under different filters, and calculate the speckle contrast of red, green, blue and white fields.
Improved YOLOv4 Power Insulator Fault Detection
Authors: Zhang Zhen , Kong Shuaihua , Peng Kun
Published: September 2021

In order to achieve accurate real-time monitoring of power insulators on transmission lines, an improved YOLOv4 network model is proposed to detect power insulator faults. Experimental results show that the mAP value of the improved YOLOv4 network model reaches 93.01%, and the detection frame rate reaches 44 frames/s. Compared with the YOLOv4 and Faster R-CNN models, it can be concluded that the proposed model can better meet the needs of power insulator fault detection for transmission lines.
A fault diagnosis equipment of motor bearing based on sound signal and CNN
Authors: Li Dong , Li Binbin , Wang Chaoqun , Cheng Pengyu , Jiao Bin
Published: September 2021

As an important part of mechanical equipment, the motor bearing damage rate is very high. In order to realize the fast and accurate diagnosis of motor bearing faults, this paper designs a fault diagnosis equipment based on sound signals. First, perform wavelet transform on the collected sound signal, then use the spectrogram generated by the fast Fourier transform to preliminarily determine whether the motor bearing is faulty, and finally use the convolutional neural network model that has been imported into the processor to diagnose the faulty parts of the motor bearing, The accuracy rate is above 98.41%.
Research on Web Robot Detection Technology for Concept Drift
Authors: Chen Xue , Song Yang , Xiong Wei , Lu Yutao , Wang Xingen
Published: September 2021

Web robots have long been significant participants of the internet and the detection is deemed to be essential. Contemporary web robot detection techniques lack the ability to detect when the characteristics of web robots drastically change over time, namely a phenomenon called concept drift. Such change of web robot’s behavior may lead to the deterioration of detection model performance. In order to maintain high detection performance over time, in this paper, we propose a novel web robot detection framework that consists of a model pool, a reinforcement learning algorithm integrating all the models and a concept drift detection module. First, we employ reinforcement learning to integrate a number of detection models that targets different types of web robots, by dynamically adjusting model weights. Then we apply the drift detection method (DDM) to monitor concept drift and identify the need to retrain the model over time. Experiments are conducted using real website datasets under concept drift. The results demonstrate that our model significantly outperforms the state-of-the-art approaches.
Modeling of multilevel control system based on Event-B
Authors: Wang Yutian
Published: September 2021

Aiming at the problems existing in the traditional development method of multilevel control system, this paper proposes a formal modeling solution based on Event-B from the perspective of practical application. Based on the analysis of four synchronization modes and the principle of multilevel control system, a formal method is introduced. On this basis, by formulating the refined strategy of the multilevel control system model, the iUML-B model meeting the security requirements is established step by step. Through the automatic transformation function of the Rodin, the iUML-B model of multilevel control system is automatically transformed into Event-B mode. In order to ensure the safety of the system, this paper uses the ProB to simulate and record the event trajectory. The results show that the formal modeling method based on Event-B greatly improves the security and development efficiency of industrial control.
Research and Application of Substation Safety Communication Based on MMS Alternative Protocol
Authors: Luo Huafeng , Shen Yifei , Xu Ai , Lu Chengyu , Ruan Lixiang , Du Qi-wei
Published: September 2021

At present, most substations are constructed based on IEC 61850 standard. The communication protocols in the station mainly include MMS, GOOSE and SMV, which are gradually exposed in engineering practice. Some deficiencies and potential safety hazards have emerged. For this reason, based on the MMS alternative protocol, the function and security of its implementation are introduced. In terms of functions, MMS alternative protocol adds multiple services and optimizes the deficiencies of the existing MMS protocol; for security, the application layer of the MMS alternative protocol implements two-way identity authentication based on the SM2 algorithm and despatching certificate, preventing unauthorized devices to prevent illegal access and attacks from the source of protocol; the transport layer of the MMS alternative protocol implements full link encryption and authentication based on the SM2 algorithm and despatching certificate to ensure the transmitted data message is antiforgery and non-repudiation and antitheft, protect the confidentiality and integrity of data messages. Therefore, the MMS alternative protocol has been greatly optimized on function, and the security authentication and transmission encryption mechanism of the protocol are focused on the security aspect. The final experimental results prove that the MMS alternative protocol has a certain reference significance in engineering applications.
Application of Pseudo-random electrical exploration method in mineral exploration: a case study of skarn-type ore body
Authors: Li Dawei , Sun Huafeng , Shi Weixin , Zhang Qiyan , Gao Pengxin
Published: September 2021

Skarn-type ore body containing rich mineral resources, which is a type of deposit with important industrial significance and a wide distribution, is formed by metasomatism of mineral gas-bearing hydrothermal fluids on or near the contact zone between intermediate-acid-medium-basic intrusive rocks and carbonate rocks. It is hard to obtain stable data by using conventional electrical prospecting method because of strong electromagnetic interference. A new pseudo-random method is used to do geological survey work in Northeast China for interference avoidance.
BeiDou-based borehole hydrological intelligent monitoring system design
Authors: Qi Yannan , Xu Lenian , Guo Chenglong , Zhang Xu , Jia Chensheng
Published: September 2021

An intelligent monitoring system for borehole hydrology based on Beidou is designed. This system uses input sensors to measure water level and water temperature in boreholes. The intelligent terminal uses the STM32F103RCT6 microprocessor as its core, and adopts a timed power-on mode of operation to collect water level and water temperature information, uploads the collected water level and water temperature data to the gateway through the Beidou module, and uploads the water level and water temperature data to the OneNET platform through the GSM network via the gateway, the OneNET platform provides intelligent statistical analysis of uploaded data, enabling real-time monitoring and early warning of water levels and temperatures in boreholes, effectively preventing and controlling water damage in mines.
Virtual simulation of EFPT-D process control experiment
Authors: Xu Likai , Wang ZhiFeng
Published: September 2021

With the development of green experiment and online teaching, using virtual simulation technology to provide experimental equipment and platform for students has become an effective choice. It can solve many problems in experimentation, such as a shortage of equipment, fast iteration speeds, etc. In this paper, Unity3d engine is used as the virtual reality development platform to simulate the liquid level setting control experiment of B&R EFPT-D process control experimental platform, which can completely restore the experimental steps, and further use the code to simulate the mathematical model and PID control algorithm, which has guiding significance for practical teaching.
Development of a finger rehabilitation robot based on sliding slot linkage mechanism
Authors: Lu Shiqing , Yong Li , Luo Lulu , Peng Yang , Tong Li , Hui Jin
Published: September 2021

Rehabilitation training for stroke patients is a technical and social problem. A new type of pneumatic finger rehabilitation robot was presented based on sliding slot linkage mechanism. Through the analysis of the biological structure of the human hand, the sliding slot linkage mechanism with characteristics of combination drive, size adjustable and safety protection was developed. The detailed structure and control system of the finger rehabilitation robot were designed. Finite element analysis of the main parts and kinematic simulation of the mechanism were performed to verify the structural strength and motion feature of the finger rehabilitation robot, respectively. Finally, the prototype model of the sliding slot linkage mechanism was fabricated and a series motion tests were conducted. Results indicate that the finger rehabilitation robot is reliable and could satisfy the requirements of finger rehabilitation training.
Design of Visual Search and Positioning System Based on Labview + PLC
Authors: Cheng Zihua
Published: September 2021

Aiming at the problem that the fixed lens cannot achieve full-area shooting recognition and obtaining the target position within the target area. This paper proposes using a moving vision lens to perform shooting recognition at fixed points and sub-regions within the set search path to determine the target object’s visual coordinates and use PID calculation to drive the actuator to complete the target workpiece grabbing. The system has high positioning accuracy through experimental verification, and the correct identification and capture can reach 100%.
Design of Ultrasonic Levitation Control System Based on FPGA
Authors: Li Ming , Cai Weibo , Tang Xiaoyu , Li Tingfeng , Zhu Linlin , Yan Yalin
Published: September 2021

As a method to achieve containerless processing, the object levitation technique has a broad application prospect in vital research fields. However, the levitation distance of Electromagnetic levitation, near-field acoustic levitation is not far enough to complete cantainerless processing, and the stability of ultrasonic levitation that use single emitter or single transductor array is still needed to be improved. Therefore, this paper proposes a new embedding electronic system based on FPGA controller to drive a construction of transducer arrays that perpendicularly formed by uniaxial concave sphere and uniaxial biplane. A phase delay algorithm is used on this system to change the position of the stand wave points to move the object smoothly. Furthermore, through experimental validation, this system has a stable signal output to reach the goal of levitation and control.
Development and practice of universal motion controller communication components for precision measurement systems
Authors: Xue Song , Bai Yuewei
Published: September 2021

The motion control system and communication system based on the motion controller, the software and hardware communication links, software, and specific hardware are bound together. The coupling between software and hardware is excellent. This paper designs a universal motion controller communication component of the three-coordinate measurement family based on COM component technology and I++ DME protocol, which is used to solve high coupling between measurement software and hardware in the measurement industry. After experimental verification, the COM communication component achieves the expected effect.
A Nuclear detection method Based on improved You Only Look Once v5s Framework
Authors: Li Jiaheng , Wang Jingcun , Feng Shen
Published: September 2021

Extracting human cell smear samples through automated scanners, using target detection algorithm to detect its nucleus is an important content in cell detection. Due to the different shapes, different sizes and complex backgrounds of nuclei in the samples, automatic detection of nuclei is a challenging task. In order to solve the problem of complex small target recognition in nuclear detection and improve detection accuracy, based on the YOLOV5S framework of one-stage target detection, make certain improvement, add new residual module to the original network Neck layer, at the same time carry on network widening operation to the subsequent framework. The algorithm visualizes the results of training and testing through Tensorboard. Experimental results show that the accuracy of the improved YOLOV5S network is 1.6% and 4.4% higher than that of the original YOLOV5S network and YOLOV3 network. the improved network has strong real-time performance and high accuracy, which can meet the actual use requirements.
A Trajectory Abnormal Detection Method Based on Segmentation and Clustering
Authors: Qin Wanting , Tang Jun , Lu Cong , Lao Songyang
Published: September 2021

The early warning of abnormal behaviour is helpful to explore the potential risk and avoid the occurrence of accidents. Therefore, it is of great significance to excavate abnormal trajectory patterns from a large number of trajectories. From the perspective of unsupervised learning, a two-level trajectory abnormal detection method based on segmentation and clustering based on segmentation and clustering is proposed in this paper. Firstly, the method considers the influence of a time factor in the stages of segmentation, and segments by the constraint of trajectory state. Then, it redefines the distance between the trajectory segments according to the temporal and spatial distance to cluster after segmentation. Finally, abnormal detection is carried out according to clustering results. In the abnormal detection phase, a two-level detection method is adopted. Firstly, the abnormal trajectory segment is found by first-level coarse-grained abnormal detection. Then, the abnormal subtrajectory segment is detected by second-level fine-grained abnormal detection. The real Atlantic Ocean hurricane data is used for the simulation experiments. Compared with the classical TRAOD detection method, proposed method is more consistent with the actual situation.
Large-scale Simulation of Unsteady Flows in 13-stage Multi-spool Compressor
Authors: Wang Ziwei , Jiang Xiong , Lu Fengshun , Liu Fan , Li Bin
Published: September 2021

Although significant advances have been made in full-annulus simulation of flow in single-spool compressors. However, no work has been devoted to full-annulus simulation of flow in multi-spool compressors. The aim of the paper is to develop techniques for full-annulus simulation of unsteady flows in multi-spool compressor. The techniques for automatic generation of large-scale full-annulus grid of multi-spool compressor, for uniting simulation in LPC(Low Pressure Compressor) and HPC(High Pressure Compressor) in one solver, for processing LPC/HPC interface in multi-spool compressor in parallel environment, for managing vast amounts of flow field data in multi-spool compressor with low space complexity are proposed. Based on an in-house software ASPAC, these techniques are then applied to full-annulus unsteady simulation of flow in a 13-stage multi-spool compressor with 800 million grid cells using 10240 processes. The numerical simulation results are validated through compared with results of empirical model. Meanwhile, it indicates that results of large-scale unsteady simulation are more precise than results of steady simulation.
Hybrid Automatic Test Technology for Spacecraft
Authors: Lv Wei , Song Hongjiang , He Xiaoyu
Published: September 2021

A new hybrid test case design and execution technology based on component and script is proposed, which combines test component with test script to form test case and realize automatic test of spacecraft. The common test logic is described by dragging components and editing component parameters; for the special and complex logic test requirements, the method of writing script is used to describe. Components and scripts can be mixed in the same test case to describe complex and changeable test cases, and can be executed automatically.
Design and analysis of planting mechanism for a self-propelled transplanting machine
Authors: Meng Xianjiang , Zhao Dong , Kong Linghui , Cai Dongmei
Published: September 2021

In order to solve the problems such as missing planting, burying seedlings and pouring seedlings of the current transplanter, a planting mechanism was designed and its function was analyzed theoretically in the paper. Firstly, the three-dimensional model of the transplanting mechanism was established; secondly, the mathematical model of the end movement trajectory of the transplanting mechanism was established and calculated using Matlab; finally, the motion simulation of the planting mechanism was carried based on ADAMS. The simulation results show that the velocity of the end of the planting mechanism is as same as the theoretical calculation. Therefore, the planting time and the seedling taking time were obtained in order to increase the planter’s movement stability and the rationality of structure.
Overview of the V International Workshop on Innovations in Agro and Food Technologies - WIAFT-V-2021
Authors: Kovalev I V , Gorlov I F , Voroshilova A A , Slozhenkina M I
Published: September 2021

The overview describes the main directions and results of the V International Workshop on Innovations in Agro and Food Technologies (WIAFT-V-2021) held in Volgograd, Russian Federation on 17-18 June 2021. It gives the details about the participants and the proceedings. The anchor partners of Krasnoyarsk Science and Technology City Hall were Krasnoyarsk State Agrarian University, the Volga Region Research Institute of Manufacture and Processing of Meat-and-Milk Production, Volgograd, Russia, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Tashkent, Uzbekistan and Bukhara Engineering Technological Institute, Bukhara, Uzbekistan. The Krasnoyarsk Research Institute of Agriculture of the Federal Research Center "Krasnoyarsk Science Center of the Siberian Branch of the Russian Academy of Sciences" and Siberian Scientific Centre DNIT sponsored the Workshop.
Optimization of onion drying process parameters using the full factorial experiment method
Authors: Kholikov Alijon , Jumaev Jura , Hikmatov Doniyor , Kuvvatov Khamid
Published: September 2021

Evaluation of the effectiveness of the influence of the main factors on drying using heat pipes, such as temperature, drying time and layer thickness of onions, was carried out for the first time using the method of full factorial experiment. For this, the variables were encoded, the experiment planning matrix was compiled, the regression equations were calculated, the equation was checked for adequacy, and a posteriori analysis was performed. The main factors influencing the drying of sliced onions in drying installations using heat pipes have been determined. The optimal mode of onion drying in a drying plant using heat pipes has been determined.
Prevention of non-enzymatic browning of white grape wines by activated carbons Granucol
Authors: Pryadikhina A , Rozhnov E , Tretyak L , Kenijz N , Denisov D
Published: September 2021

The relevance of the conducted research is regulation of reactive phenolic compounds content in grape wines – as those reactive phenolic compounds induce the non-enzymatic oxidative browning, which can be prevented by using sorption substances, in particular, activated carbon. The purpose of the research is to study the effect of activated carbons Granucol on the chromatic and organoleptic properties of dry grape wine materials from Crystal variety grapes at various dosages. As a result of the conducted research, the expediency of using Granucol activated carbons to increase the sensory properties of grape wines and to increase the wines shelf life has been proved. The chromatic properties were studied in accordance with the current guidelines of the International Organization of Vine and Wine (OIV, France). As an additional indicator for assessment of the wines color, the calculated value of the wine yellowness was used. It has been shown that treatment of wine with activated carbons Granucol allows efficient regulation the wines color properties and major elimination of undesired tones in wines flavor, thus improving the harmony of wines in whole.
Qualitative purification of pomegranate juice using electro flotation
Authors: Barakaev N R , Kurbanov J M , Uzaydullaev A O , Gafforov A X
Published: September 2021

The article describes the research conducted on qualitative cleaning of pomegranate juice using electro flotation, method of cleaning juice, also results of conducted experiment and other results related to this research. As a result of the research, it was found that the method of electroflotation provides effective irrigation of pomegranate juice. Factors affecting the electroflocation process were determined and their alternative values were found. Organoleptic analysis was conducted with the participation of scientific staff and showed that electroflotation processing improves the appearance and taste of pomegranate juice.
Improvement of the technology for the production of semi-finished meat products
Authors: Alekseeva Y A , Garmaev D Ts , Khoroshailo T A , Martemyanova A A
Published: September 2021

Chopped semi-finished meat products are portioned minced meat products based on raw meat, which are produced in a colossal assortment. The types of such semi-finished products, depending on the raw materials used, are divided into: naturally chopped semi-finished meat products made exclusively from meat raw materials; chopped semi-finished meat products, which, in addition to raw meat, include bread products, soybean additives, various cereals, vegetables. Almost all chopped semi-finished products are manufactured according to technical conditions that must meet the requirements of the main regulatory documents applicable to all food products established on the territory of the Russian Federation. Namely, manufacturers themselves develop a recipe for the production of semi-finished products, trying to reduce costs, using raw materials of poor quality or replacing meat raw materials with vegetable ones. This leads to a decrease in product quality. Therefore, it is necessary to pay special attention to the composition of semi-finished products and in their production strictly comply with the current regulatory documents.