bluuebunny/crossref_metadata_2025 huggingface dataset:
Fluid-Structure interaction framework based on structured RANS solver
Authors: Cinquegrana Davide , Vitagliano Pier Luigi
Published: February 2021

A Fluid Structure Interaction framework developed at CIRA to deal with multi-physics problems in a partitioned approach is presented. The CIRA multi-block structured flow solver for unsteady Navier-Stokes equations UZEN was updated and tightly coupled with an open-source solver for non-linear structural dynamics in a modular approach. The solvers are glued in space and time through an open source library, able to control the executing processes and to deliver exchanging data by specific adapters. The validity of the framework is tested on vortex-induced vibration effects of a cantilevered beam in low Reynolds flow and on as three-dimensional wing flutter in transonic turbulent flow.
Dynamic Models of Satellite Relative Motion and their effects on Kalman Filter
Authors: Imran Ali , Xuechuan Wang , Xiaokui Yue
Published: February 2021

In this paper we will study the effects of an increasingly complex Kalman filter state transition matrix on the accuracy of the estimation of a non-linear relative navigation system. The propagation model will be constant in all the cases. The measurements are generated using Xu-Wang model and then noise is added. Whereas the process non-linear vector function/propagation matrix of the Kalman filter will be modified. In the first scenario the Clohessy-Wiltshire equations are considered as the basic propagation model of the Kalman Filter. In the second scenario the eccentricity of the chief satellite’s orbit is included in the model of the Kalman Filter. In the 3rd case we are using the model presented by Xu-Wang which incorporates the oblateness of Earth into the Tschauner-Hempel model. The divergence of the Kalman Filter is studied and provides a guideline to design engineers.
Hypersonic boundary layer receptivity on flat plate with blunt leading edge due to acoustic disturbance
Authors: Zhang Yifeng , Chen Jianqiang , Yuan Xianxu , Chen Xi , Xiang Xinghao
Published: February 2021

In the process of hypersonic boundary layer transition, the leading edge receptivity due to free-stream acoustic disturbance provides unstable perturbations in boundary layer with initial amplitudes, which is one of hot issues in the study about transition mechanism. The receptivity of leading edge is influenced by many factors, involving geometry parameters, disturbance types, etc., among which the bluntness plays a key role for generating disturbances. In order to reveal the mechanism of bluntness influence on the boundary layer transition, investigations into the acoustic receptivity on flat plates with sharp and blunt leading edge are carried out. The flow conditions are as follows: Mach number 6, Reynolds number 1e7/m, adiabatic wall. By introducing two-dimensional plane fast and slow acoustic waves into the free-stream, the whole receptivity process of free-stream disturbances passing through shock wave into boundary layer is simulated with high-order accuracy DNS method. With sharp leading edge as a reference, the generation mechanism of the perturbations near blunt leading edge and its influence on the boundary layer downstream are analyzed. Some conclusions are obtained: for acoustic disturbances in hypersonic free-streams, the receptivity mechanism of blunt leading edge is different from that of sharp leading edge; both the fast and the slow mode can be produced respectively near the sharp leading edge by the fast and the slow acoustic wave, while only fast mode appears near the blunt leading edge; the receptivity of blunt leading edge due to the fast acoustic is stronger than that due to slow acoustic, and is also stronger than that of the sharp leading edge in a certain region of boundary layer downstream.
An intelligent polynomial chaos expansion method based upon features selection
Authors: Zhang Wei , Wang Qiang , Yan Chao
Published: February 2021

Polynomial chaos expansion (PCE) method is a common tool for uncertainty quantification (UQ) in fluid mechanics. However, there exists ‘Dimensional Curse’ when the parameters dimension is very high, and large samples are required to solve the PCE function. This would hinder the application of PCE in high dimensions. An intelligent PCE method based on the idea of features selection in machine learning is proposed in this paper. Therefore, only several important features will be selected to construct the PCE function, then fewer samples will be needed to solve the model, and it will be more efficient. Several benchmark functions and an RAE2822 airfoil flow case are utilized to verify the UQ capability of the intelligent PCE. It is proved to be more efficient than the original PCE, with nearly same accuracy.
Bayesian uncertainty analysis of SA turbulence model for backward-facing step simulations
Authors: Jin-ping Li , Ma Ming , Yan Chao
Published: February 2021

The Reynolds averaged Navier-Stokes models are still the workhorse in current engineering applications due to its high efficiency and robustness. However, the closure coefficients (also known as model parameters) of turbulence models are calibrated by model builders according to some fundamental flows, and the values suggested by the model builders may not be applicable to all flow types. In this work, the Bayesian method is applied to recalibrate the closure coefficients of SA turbulence model to improve its performance in backward-facing step problem. The results show that the four parameters Cb1, Cw3, Cv1and κ are well informed by the experimental data of skin friction coefficient. The recalibrated model parameters show better performance than the nominal values in the prediction of skin fiction coefficient.
Multi-dimensional dissipation strategy within advection upstream splitting methods in hypersonic flows
Authors: Shu-sheng Chen , Yang Hua , Fang-jie Cai , Zheng-hong Gao
Published: February 2021

The work develops the multi-dimensional dissipation strategy within advection upstream splitting methods (AUSM) in hypersonic flows based on the affordable shock-stable item by Chen et al. (J. Comput. Phys. 373 (2018) 662-672). This strategy is related to the sear velocity difference and the pressure-based sensing function. It strengthens the robustness of AUSM-family schemes against shock anomalies and meantime preserves shear layer. A series of numerical cases illuminate its potential capability for hypersonic flows, particularly in the extreme situations such as the large aspect ratio of cells, skewed non-orthogonal grid, and unstructured grid.
Transition prediction with hypersonic cross-flow model on HIFiRE-5
Authors: Xing-hao Xiang , Hai-jie Ren , Yi-feng Zhang , Xian-xu Yuan , Jian-qiang Chen , Shu-sheng Chen
Published: February 2021

The work develops a localized hypersonic cross-flow transition criterion considering the influence of cross-flow intensity and surface roughness. A cross-flow extension of hypersonic modified γ-Re θ transition model based on Chant2.0 computing platform is implemented. The extended transition model is used to predict the cross-flow transition on the elliptic cone (HIFiRE-5) in multiple states, and the predicted results are in good accordance with the experimental results.
Linear transfer guidance based on Lyapunov method
Authors: Bai Shengzhou , Han Chao , Sun Xiucong
Published: February 2021

Low-thrust propulsion technology is widely used in space missions. However, traditional methods are not appropriate for the general case. In this study, a linearization Lyapunov method for constant thrust control is proposed. Based on relative orbit elements (ROEs), analytical constant-thrust linear equations are introduced. Moreover, via Lyapunov method, the linear constant-thrust control strategy is obtained. Numerical simulations are conducted to demonstrate the validation of the proposed method. Given different thrust magnitudes, the accuracy meets the requirement in these cases. Thus, it proves to be a practical choice for engineering applications.
DOA estimation for coherent distributed sources based on common spectral peak search
Authors: Li Hao , Bai Yi , Jian Chunxiao , Xu Haiyun , Mei Fengtong
Published: February 2021

Most of the existing DOA estimation algorithms are based on uniform array, whose estimation performance is limited by the shortcoming of small aperture of uniform array, and it is difficult to apply sparse array to DOA estimation of distributed sources. In order to solve the above problems, this paper introduces interqualitative array into DOA estimation of distributed sources, and proposes a DOA estimation algorithm for coherent distributed sources. Because the array element spacing is larger than half wavelength, the direct estimation will produce false peak. In order to eliminate the ambiguity, this paper proves that DOA estimation of two submatrices is performed separately, and its common value is unique, that is, the true incidence Angle. According to this proof, DOA estimation of two submatrices is carried out separately for the one-dimensional DOA estimation scenario of distributed sources, and the common part of the two sets of estimation results is taken as the final estimation result. The complexity analysis and performance verification of this method are also given. Simulation experiments show that the performance of the proposed method is better than that of the DSPE algorithm and TLS-ESPRIT algorithm under the same array number in the one-dimensional DOA estimation scenario.
The integration and development trend of China’s 5G technology and smart cleaning
Authors: Ji Huiying , Huang Hongtao
Published: February 2021

China’s 5G development has achieved a significant leap from the conceptual level to the application level from technical testing and pilot implementation in 2018 to official commercial use in 2019. In 2020, China will accelerate the application of new technologies such as 4K/8K, VR/AR, and increase the supply of high-end information services.At present, the works in this field stay in the imagination of 5G smart and clean level, talking about the grounded products under the 4G foundation, and fail to reflect the technological attributes of China’s 5G application. This article further analyzes the latest applications and development trends of 5G technology in the field of smart cleaning, which is an important theoretical basis for promoting the intelligent and modern development of China’s cleaning industry, and will help the development of smart cleaning industry and the construction of smart cities in China.
Development of dual-polarization weather radar products display platform
Authors: Zhang Qian , Zhang Peng , Zhang Yi , Zheng Yi , Wei Haiwen , Wei Yupeng , Yang Chuanfeng
Published: February 2021

Dual-polarization weather radar is more advanced than doppler weather radar, with higher observation accuracy and more products. Using PHP and Dreamweaver to develop dual-polarization weather radar products display platform. The dual-polarization weather radar products display platform can display ZDR, CC, KDP, HCl, QPE and other dual polarization radar products in real time, and has the function of playing back 30 times products in the past three hours of a single product. Using this platform, forecasters can compare and analyze doppler radar products with dual-polarization radar products to grasp the real-time conditions of short-term strong convective weather better, to improve the accuracy of short-term forecasts, especially disastrous weather forecasts, so as to further exert the advancement and superiority of dual-polarization weather radar. After applications, it shows that the dual-polarization radar products display platform is reliable and stable operation.
Design of embedded application software of 3D camera based on line laser
Authors: Zhang Lei , Zhang Suofei , Yang Hao
Published: February 2021

The embedded application software of the line laser 3D camera running on the Xilinx Zynq7000 SoC which is the control of circuit to extract and transmit the centre of the laser stripe in the line laser 3D contour scanning system to the PC was designed. First, by analysing the functional requirements of the system, a modular software structure for real-time multitasking is proposed, and then the program flow chart, which mainly includes a data acquisition module, parameter configuration module, communication module, and system management module. The system provides two data acquisition channels, namely the original image and the centre point coordinate data, which is convenient for system setup and debugging, and realizes the adjustment of ROI in different scenarios. It has the functions of real-time acquisition of line laser centre point coordinates and online configuration of camera parameters. The debugging of each module can work stably and reliably.
Investigations of different Eu2O3 concentration and synthesizing temperatures on the photoluminescence properties of Sr3Al2O6 phosphors
Authors: Fan Yu , Chen Chin-Ta , Chen Ying-Jun , Lin Pei-Ying , Yang Cheng-Fu
Published: February 2021

x Eu2O3-doped Sr3Al2O6 powders(x=0.0025, 0.005, 0.0075, and 0.01) are synthesized in air using a solid state reaction method. From XRD patterns, we find that the SrCO3, Al2O3, and Sr3Al2O6 phases are observed in all 1000°C-synthesized x Eu2O3-doped Sr3Al2O6 powders, and the diffraction intensities of SrCO3 and Al2O3 phases decrease and that of Sr3Al2O6 phase increases with synthesizing temperature, and SrCO3 and Al2O3 phases disappear at 1200°C and 1300°C, respectively. When we use 240 nm as excitation wavelength, all the photoluminescence (PL) spectra of x Eu2O3-doped Sr3Al2O6 phosphors show that two apparent emission peaks are at wavelengths of 592 nm and 612 nm and one unapparent emission peak is at wavelength of about 658 nm, which are recognized as the 5D0→7F1, 5D0→7F2, and 5D0→7F3 transitions of Eu3+ ions. The emission intensity of main emission peak (592 nm) of x Eu2O3-doped Sr3Al2O6 phosphors is affected by synthesizing temperature and Eu2O3 concentration, and the concentration quench effect is also observed.
Research on application of corner detection in thread vision measurement
Authors: Feng Zibo , You Fucheng , He Junwei
Published: February 2021

With the rapid development of the automation field, automatic inspection of fasteners in the aviation field has become a top priority. It is precious to realize the fast measurement of important information in fastener production by non-contact. This paper aims to detect the optical image detection of the external thread angle of fasteners. We analyze the traditional Ramer algorithm’s contour segmentation steps in separating thread edge from thread bottom arc to obtain accurate thread angle size and thread bottom arc radius. And Harris algorithm is proposed to find corners again by comparison. Finally, using a discrete point curvature to verify the Harris algorithm’s accuracy in corner detection. Meanwhile, by comparing the edge fitted thread angle with the measured thread angle to verify the Harris algorithm’s reliability in corner detection.
Semantic applications for ontological information theory
Authors: Alnahdi Amany K.
Published: February 2021

Information theory is a field that has applications in several scientific domains. This field, which was initially proposed by Claude Shannon, is interdisciplinary; it combines probability, electrical engineering, information engineering, computer science, and statistics. Representing knowledge in information theory provides scientific scholars a resourceful reference for the filed. By learning the precise terminology used in information theory, researchers can discover documents in the domain. In addition, they can communicate knowledge and ideas by using the accurate jargon. A scientific ontology representing knowledge corpus can be implemented digitally by articulating the concepts in the domain of information theory using semantic graphs. These scientific semantic artifacts are valuable with Web 3 technologies. They facilitate searching documents online by providing precise related results. In addition, it is expected that the semantic knowledge to be applicable in Web service applications based on information theory as Web services are software components that communicate information. This work presents an ontology for the Information theory. The ontology conceptualizes the knowledge of information domain by identifying the main concepts, principles, equations, metrics, and history of information theory. The ontology composed of classes, instances, and properties is built using protege, an ontology editor, and is stored in OWL format. Educational applications for the built ontology are indicated.
Lightweight identity authentication scheme for IoT devices based on blockchain
Authors: Ma Wanli , Zhang Qi , Ma Junwei , Xue Honglin , Hao Xiaowei , Li Haitao , Jia Weidong , Meng Yaning , Wen Zhifang , Zhang Jianliang
Published: February 2021

Aiming at the resource limitation and security problems of Internet of things devices, a lightweight identity authentication scheme is proposed. In the scheme, the identity authentication model is designed, and the model is implemented by using the blockchain smart contract. Through the analysis, the scheme can effectively complete the identity authentication under the condition of limited equipment resources.
Construction of real-time mental health early warning system based on machine learning
Authors: Liao Suqun , zhang Qizhi , Gan Rui
Published: February 2021

With the great development of computer technology, it is feasible to apply robot learning to the prediction and diagnosis of mental illness. Establishing an online psychological health warning system helps psychologists to know the mental health status of patients and makes rapid intervention. Based on the principle of machine learning, the design idea of constructing online psychological early warning system were proposed here by using the patient’s daily performance and textual representation. The system included: client, server, doctor, and family. The client collected user text data and offered basic client technology; the server provided business logic of the web backend, database and mental health rating warning for client, doctor and family; the doctor mainly displayed the binding user status. When the mental health level of users was poor, early warning should be warning so that doctors can intervene in time. The relevant auxiliary treatment information for the patient would be send to family side, which help for the family therapy. This system provides a new way for doctors to monitor patients with mental illness, which but further study and training is needed to establish an effective model.
Visual image encryption scheme based on BTC and LSB modification
Authors: Liu Chengyu , Zheng Sifei , Feng Zijing , Chen Riqing , Liu Xiaolong
Published: February 2021

With the rapid development of Internet technology, information security issues have become an important guarantee for society. Image encryption technology can achieve security by converting images into other unrecognizable formats. Many existing visible image encryption methods are not highly visual, which not only causes the leakage of important image information, but also easily causes a waste of resources. In order to solve this problem, this paper proposes a new visual image encryption scheme based on BTC compression. The original image is protected by converting the original image into other formats that ordinary users cannot recognize to achieve the security level required by the user. The experimental results show that the proposed scheme is not only simple and convenient, but also has excellent performance in terms of compression rate and visual distortion. It has been widely used by many researchers.
Reinforcement learning based self-adaptive moving target defense against DDoS attacks
Authors: Gao Chungang , Wang Yongjie
Published: February 2021

In the research of moving target defense technology, the formulation and evaluation of network offensive and defensive game strategy have become a current research hotspot, but there are still some urgent problems to be solved, such as how to adjust the defense if the attacker’s strategy is constantly changing during the offensive and defensive game strategies to deal with its changes and how to balance system security and system performance when system resources are limited. Aiming at DDoS attacks, this paper proposes a moving target defense adaptive strategy based on reinforcement learning, which can adaptively adjust defense strategies according to changes in environmental conditions, while balancing system security and system performance through parameter adjustments to adapt to different scenarios. The simulation experiment results show that the proposed model and method are feasible and effective.
Latency minimization for the MEC-aided vehicular network under Doppler Effect
Authors: Du A Y , Wang P , Song L
Published: February 2021

In this paper, we consider a heterogeneous Mobile Edge Computing (MEC)-aided multi-layer vehicular network consisting of multiple vehicles as Edge Device (EDs), a road side unit (RSU), and a cloud center (CC). The raw data produced by the vehicles can be processed at the three nodes separately. EDs transmit the data to the RSU via wireless communication link, and a wired link is considered between the RSU and the CC. Taking the mobility of vehicles and the limited amount of resources into account, we jointly discuss the task offloading and resource allocation in this three-layer MEC-aided vehicular network. Specifically, the interactions of Doppler Effect and the bandwidth provided by RSU to different vehicles are investigated. Aiming at minimizing the latency while increasing the utilization of resource, we design an iterative task assignment and resource allocation (ITR) algorithm. The simulation results indicate that: 1) The average latency of all tasks is significantly decreased, and the optimal bandwidth allocation scheme to the EDs is achieved; 2) Due to the Doppler Effect of vehicles, it is important to consider both the mobility of vehicles and the length of communication links when allocating resource.
An image encryption algorithm based on SM4 and Base64
Authors: Chen Jingjing , You Fucheng
Published: February 2021

In recent years, with the continuous development of international cryptographic standards, China has also paid more attention to the design and development of cryptographic algorithms. To guarantee the security of commercial passwords, China’s National Commercial Password Management Office has formulated a series of cryptographic standards, including SM1 (SCB2), SM2, SM3, SM4, SM7, SM9, Zu chongzhi Sequence Cryptography (ZUC) and so on. Compared with other cryptographic algorithms, the SM4 cryptographic algorithm has higher security features, and its performance of cryptographic indexes can be in line with international standards. It can resist differential attacks, linear attacks and other common attacks, so it has received complete attention and application. Nowadays, the network is becoming more and more developed, and the security problem of image stream data is also becoming more and more serious. Therefore, this paper proposes an image encryption algorithm based on SM4 and Base64, which outputs the RGB values of each pixel into a matrix, and then encrypts and decrypts them using SM4 and Base6 encoding and has higher reliability and more substantial anti-attack capability in the image transmission process.
The Modeling and Simulation of Chaff Release at High Speed
Authors: Tong Jijin , Liu Zhong , Xu Liqin
Published: February 2021

Commonly, chaff cartridge release the chaff based on detonating the dynamite or blasting form projectile. In order to improve the scatter effect of chaff, a novel technique of chaff release is proposed, which is be carried by a given carrier revolving around an axis at high speed. And the model of chaff motion in the phase of dispersing rapidly is established on the basis of the analysing the influence of resistance, gravity and viscous force. Simulation instance show that the method based on revolving carrier is efficacious, and some useful revelation can be elicited from the simulation. The research in this paper has great significance for the research and engineering implementation of gun launched chaff jamming projectile.
Simulation Calculation and Analysis of the Influence of Wake Jet on Aircraft Tail Flow Field
Authors: Liu Wenlin , Zhou Pengyu , Yu Xiongfei , Song Zhijie , Wang Jinku
Published: February 2021

In order to analyze the influence of the wake jet on the tail flow field during the take-off and landing phase of the aircraft, this paper uses Computational Fluid Dynamics technology, takes an aircraft as the research object, and uses the RANS equation, Realizable k-ε turbulence model and the Delaunay unstructured meshing method. The Roe discrete scheme is used to numerically simulate the wake field of the aircraft using the coupled implicit algorithm, which is divided into two conditions: wake jet and no wake jet. The simulation results show that there is a certain back pressure zone in the wake field of the aircraft, the gauge pressure range is -272∼1067 Pa, the pressure difference at the same position in the wake field area is small, the range is -240∼60 Pa, and the wake field pressure has little correlation with the wake jet, and there is no separation vortex under the two conditions. The simulation results verify the rationality and effectiveness of the simulation calculation, and provide a certain theoretical reference for the safe take-off and landing of the aircraft.
The Mathematical Model and an Genetic Algorithm for the Two-Echelon Electric Vehicle Routing Problem
Authors: Zhang Yue , Zhou Shenghan , Ji XinPeng , Chen Bang , Liu HouXiang , Xiao Yiyong , Chang Wenbing
Published: February 2021

In order to cope with the challenges of high cargo load and high timeliness distribution in logistics industry, as well as to alleviate the current situation of oil resource depletion and air pollution, this study established a mathematical model of two-echelon electric vehicle routing problem (2E-EVRP) and design a heuristic algorithm. The 2E-EVRP can be divided into the multiple depot vehicle routing problem (MDEVRP) and the split delivery vehicle routing problem (SDVRP). The proposed genetic algorithm is used to solve the MDEVRP, and the actual case of a logistics company in Beijing is taken as the calculation experiment, so as to verify the feasibility of the proposed algorithm and provide decision-making reference for the development of logistics enterprises. The results show that the total path length obtained by the proposed algorithm is optimized by 20.82 kilometers compared with the traditional simulated annealing algorithm.
New Structure of a Special Pentaprism Designed by Simulation for Orthogonal Phase Microimaging
Authors: Liao Jingrong , Wang Yawei , Zou Yang , Han Hao , Xu Yuanyuan
Published: February 2021

Quantitative phase imaging (QPI) has a very important application in the nondestructive imaging of biological cells. In view of the complex structure and various devices of imaging optical structure in traditional dual-channel orthogonal QPI, a new structure of a special pentaprism is designed as the main body of the orthogonal dual-channel phase microscopic imaging based on simulation design. In this dual-channel orthogonal QPI light structure, a hollow channel is designed as a sampling channel inside the pentaprism, a single light source through deflection of the pentaprism can form orthogonal dual-channel beams, with optical lens after diffraction modulation can form orthogonal dual-channel interference, the orthogonal dual-channel wrapped phase microscopic images are imaged on the sensors. The emulational and experimental results show that this design greatly simplifies the optical structure, uses very few optical devices, and the imaging path structure is compact and stable. With the use of single light source, the imaging quality of the dual light path has been significantly improved, which can provide a new technical basis for the improvement of biological cell (3-D) imaging technology and its instrument advancement.
Docupling Control of High Power Factor Inverter without Electrolytic Capacitor SRM Driver Simulation
Authors: Sun Baojiang , Huo Wenli , Gao Jinjian
Published: February 2021

DC bus electrolytic capacitors influential on the life of Switched reluctance motor (SRM) due to their chemical properties. For the drive system without electrolytic capacitor SRM, the power decoupling type without electrolytic capacitor scheme is studied. The parallel bidirectional Buck/Boost compensation circuit is a power decoupling circuit, a feed-forward control strategy for output voltage fluctuations of the electrolytic capacitor PFC circuit. The inverter side uses the voltage hysteresis control to stabilize the DC bus voltage. During the two-phase adjacent commutation period, the measured DC bus voltage is compared with two predetermined high and low voltages, make the DC bus voltage fluctuate within a certain range. The effectiveness of the control strategy is verified by electrical tools. The grid-side power factor is 0.958, and the grid current harmonics meet the EN61000-3-2 standard.
Study on Temporal Consistency Detecting in Coordinated Model Navy Aviation Operation Based on STN
Authors: Ma Haiyang , Zhu Huayuan , Ji Yunfei , Liu Yang , Chen Rong
Published: February 2021

The coordinated operation of navy aviation is complex and there may be hidden time conflicts. On the basis of the previous research work, this paper detected the conflicts of the time coordinated model of a sea-borne strike. Referring to the theory of temporal constraint network (STN), the paper converted the time conflicts detection problem from consistency detecting to negative cycles detecting in STN model and designs consistency detecting function based on BFCT algorithm and FIFO queue. Then, the conflict detection of coordinated actions was realized under specific combat cases and assumptions.
Research on Military Logistics Ecosystem Based on Big Data
Authors: Wan Fei , Li Rui , Qi Lei
Published: February 2021

With the arrival of the era of big data, the mature use of cloud computing and data mining technology, the big data mode have been widely applied in logistics. For military logistics, a smart military logistics ecosystem is built combining with big data, cloud computing and data mining. The collection, processing, mining technology of big data in military logistics are introduced. The promoting role of big data on military logistics is emphasized. The fusion method of big data and military logistics is expounds. The basic framework of smart military logistics ecosystem is built, and the application prospect of smart military logistics ecosystem is described.
Three-channel Synergetic State Observer for Data Transmission System with Chaotic Dynamics
Authors: Mushenko A S , Zolkin A D , Yatsumira A I
Published: February 2021

The paper presents the first developed procedure of state variables three-channel observer design for a nonlinear dynamic system. The state observer allows to estimate the values of parameters that are not available for direct measurement. Here, the observer is used to build a data secure communication system with a chaotic carrier bearing signal. As a chaotic carrier generator, we use the model of the novel chaotic attractor. The data transmission system is implemented by nonlinear mixing of useful signals into parameters of the chaotic generator model on the transmitter side and by reconstructing the useful signals on the receiver side with the designed state observer. The introduction of the state observer into chaotic generator data transmission system provides the system implementation without the use of chaotic synchronization. We provide step-by-step general description for a synergetic state observer design as well as example of the chaotic carrier bearing signal observer design procedure along with closed-loop system computer simulation results.
The Architecture Design and Implementation of Aircraft Structural Fault Assistant Decision System Based on Data Analysis
Authors: Liu Xu , Wang Haidong , Ma Haiyang , Wang Liming , Wang Li
Published: February 2021

That the aircraft structural damage diagnosis and prediction is very important for flight safety. In this paper, the aircraft structural damage can be predicted based on the maintenance data analysis and the structure fault diagnosis and assistant decision are realized. Thus, the maintenance management of aircraft structure damage can be developed. According to the actual service data, both the structural damage prediction and decision assistant support system are designed, which apply the micro-service architecture and Vue.Js front-end development technology. Thus, the effective container server and excellent usability are achieved.
Face Recognition Based on Haar Like and Euclidean Distance
Authors: Wu Hao , Cao Yu , Wei Haiping , Tian Zhuang
Published: February 2021

In order to improve the recognition rate of multi-face image, this paper proposes a face image recognition method based on haar-like and Euclidean distance. First of all, the initial features of Haar are moved in the image and gradually enlarged, the pixel sum of the feature area is obtained quickly by using the integral graph. The Haar feature is obtained by calculating the difference between black and white pixels in the feature region, and the threshold of weak classifier is calculated. Then, the extracted facial feature data is trained and classified to form a cascade classifier for face detection. Finally, the face of the image to be detected is compared with the training samples by using Euclidean distance. The experimental results show that the time of one attendance is 5-10 seconds and the success rate of face recognition is 91.1%, which verifies the advantage of the algorithm in improving the efficiency of attendance.
Data Investigation and Analysis Based on Grounded Theory
Authors: Song Bei , Xiao Fuliu
Published: February 2021

The task of building rural teachers team is an important part of the rural revitalization strategy and the key to developing local education. Based on grounded theory approach, theoretical sampling was applied in semi-structured interviews of teachers in 12 counties (cities, districts) of minority region in southwest Guangxi. In this study, through the survey data analysis and coding ,through open coding, axial coding and selective coding on the interview data, we found some problems in the minority region of southwest Guangxi such as shortage of teachers, structural imbalance, poor teaching quality, unsuitable training mode. To tackle these problems, we propose some solutions to the development of excellent teachers team and the directional and localized training that highlights national advantages in order to provide a good reference for the development of the rural teaching body in China’s minority regions.
Diffie-hellman Protocol on Raspberry pi
Authors: Wang Yuwen , Mogos Gabriela
Published: February 2021

Cryptography is a technique that applies the number theory to maintain information security. Securing data often means encrypting it. Each of the known cryptosystems has advantages and disadvantages. The most popular key exchange protocol is the Diffie-Hellman protocol. The paper presents the obtained results of the Diffie-Hellman protocol’s implementation on portable devices, namely on raspberry boards.
Voluntary Regulation and Dynamic Optimal Environmental Kuznets Curve
Authors: Zuo Hui , Ai Danxiang , Yang Jun
Published: February 2021

In this paper, we introduce a dynamic model to analyse the optimal environmental Kuznets curve. The model can be optimized with the dual constraint of environmental change and factor input growth, improving the current method of single constraint optimization in most literatures. Both environmental regulation and economic growth rate are considered and optimized. This dual optimization is quite different from the other research work, which usually only takes the former as the target. We found that there is a correlation among the intensity of environmental regulation, the economic growth rate under regulation and the endowment of environmental factors. Compared with the economy with scarce environmental factors, the economy with abundant environmental factors needs stronger environmental regulation, but the economic growth rate can be realized under environmental regulation is smaller. With the extension of growth cycle, the economic growth rate and pollution change speed under different environmental factors endowment converge.
Research on Performance Appraisal Method in Internet-based Working
Authors: Lu Hongze , Zhao Peng , Liu Shiwei
Published: February 2021

This paper summarized the difficulties of performance appraisal on Internet-based working, analized the objectives and principles of performance appraisal, the advantages and disadvantages of typical performance appraisal methods. A universal performance appraisal method in Internet-based working was proposed. It includes setting variable performance appraisal target, using Internet tools to manage performance data and supervise performance process, setting up quantitative and qualitative differentiated indicator system for different type of employees, timely feedback of Internet-based working performance appraisal indicator system. In order to check whether the method is suitable, three typical industries were selected and conducted inquiry interviews with the HRs of the companies including securities brokerage, online education, VC/PE Investment. It was found that the method can be applied to not only three industried mentioned but also other industries.
Computer Vision Based Research on PCB Recognition Using SSD Neural Network
Authors: Li Dashuang , Xu Lei , Ran Guangzai , Guo Zhanling
Published: February 2021

Printed circuit board (PCB) is an important component in the information technology industry, during PCB board assembly process, jack localization and recognition is particularly important. In view of the problem that the accuracy of target detection is not ideal, this paper applies deep learning convolutional neural network framework SSD (single shot multibox detection) to PCB element detection. By obtaining a large number of original PCB images, creating semantic label image dataset, feeding them into neural networks, and adjusting the hyperparameters, the best classification accuracy and localization accuracy are achieved. At the same time, the advantages of different algorithms are analysed after tests with other deep learning network methods. Experiments show that the SSD deep learning algorithm can realize accurate detection process of jack localization and classification, which is better than other algorithms.
An Efficient CU Partition Algorithm for VVC Intra Coding
Authors: Zhang Dongqi , Li Qiang
Published: February 2021

VVC currently under development is the latest video coding standard. VVC adopts many new coding technology or improve the original technology to enhance the coding efficiency on the basis of HEVC, at the cost of significantly increased computational complexity, which limits the industrialization and application of the VVC. To address this issue, an efficient CU partition method is presented. This method can effectively reduce computational complexity while preserving encoding efficiency. The proposed method utilizes the texture information and residual coefficient distribution of the CU to skip the low-probability CU partition types in advance. Experimental results illustrate that under the common test conditions, our proposed fast algorithm achieves 52.3% of the coding time saving while the BD-BR only increases by 1.31%, and the objective quality of the video remains basically unchanged.
Behavior Trend Analysis Method of Software Runtime Environment Elements Based on ARIMA
Authors: Li Qiuying , Lu Minyan , Gu Tingyang
Published: February 2021

Behavior trend analysis method based on auto-regressive integrated moving average (ARIMA) is presented for software runtime environment elements (REEs). The history data of environment element behavior is collected to build behavior trend analysis model. Then, behavior trend of environment elements is predicted before the environment elements actually change. Thus, according to the analysis results, we can determine the corresponding adaptive strategy before the environment elements actually change, which provides a reference for the selection and implementation of active adaptive strategy for the self-adaptive software.
Integrated Computational Learning Algorithm for Undergraduates’ Academic Early Warning
Authors: Sheng Xiaoguang , Yang Qirui , Han Yu , Wang Ying
Published: February 2021

With the development of education big data, it is helpful for education managers to use machine learning method to predict students’ academic warning status, in order to ensure that students pass the course and graduate on time. Although significant progress on predicting academic warning status has been achieved in recent years, existing methods are often lack of generalization and are difficult to be applied in real scenarios. In this study, we divide students’ scores into five coarse-grained dimensions: mathematics, foreign language, humanities, major and total score, and innovatively use machine learning ensemble model to predict college students’ academic status. Experiments show that the coarse-grained dimension division is not only conducive to the generalization of the model, but also improves the accuracy of prediction academic warning status by 9.708%. Meanwhile, experimental results show that the multi machine learning model ensemble technique can effectively improve the prediction accuracy of college students’ academic warning status. With only a small number of samples, the accuracy of predicting students’ academic warning status by three months in advance reaches 97.52%, and that by the previous semester reaches above 97.93%.
Image Segmentation Based on Improved Unet
Authors: Li Xiaojin , Qian Wenhua , Xu Dan , Liu Chunyu
Published: February 2021

In order to help doctors diagnose and treat liver lesions and accurately segment liver images, this paper proposes an improved Unet network, which adds compression extraction modules and full-scale connection blocks, extracts input image features, and achieves accurate segmentation of liver images. The compression extraction module distributes weights to convolutional layers of different sizes, which is conducive to the extraction of image spatial information and context information. Full-scale blocks are connected by skipping,combining the higher semantic information from the decoder and corresponding the lowwer semantic information from the encoder to strengthen the ability to extract tumor edge information. This article includes 25 cases from the Lits liver dataset. The dataset is classified as the training dataset and the test dataset, and the image blocks are extracted after gray-scale normalization and input to the network to acquire the final segmentation results. The segmentation result is evaluated by F1 score. Comparing multiple sets of experiments, compared with general network structures such as Unet and AttenUnet, it shows that the network architecture proposed in the Dissertation improves the accuracy and efficiency of liver image segmentations.
An Image Processing Method: Edge-guided Directional Walk Mean Smoothing
Authors: Wang Chengxue , Qian Wenhua , Xu Dan , Li Ke , Pu Yuanyuan
Published: February 2021

Image denoising is an important computer vision task, it is also the basis of many other high-level vision tasks. Recently, various image denoising algorithms have proposed, such as BM3D, sparse representation and deep learning, that have achieved impressive performance in AWGN denoising or blind denoising tasks. However, when dealing with Dongba painting (A traditional painting from China’s ethnic minorities), there are problems that Dongba painting have blurred edges and faded colors, it is important to retain its original style when denoising. In this paper, we propose a novel image post-processing technique termed edge-guided directional walk mean smoothing (EDWMS), it can effectively calculate the mean of pixels along different directions then obtain denoised image with sharp edge. Experiments show that the proposed EDWMS outperforms compared algorithms in both edge sharpness and color saturation.
Management of MicroGrid in Power System in the Perspective of Communication Process of Multi-agent System
Authors: Sun Shumin , Cheng Yan , Wei Dajun , Wang Nan
Published: February 2021

Nowadays, The microgrid(MG) provides a way for the stable access of many kinds of distributed energy to power grid, and multi-agent system(MAS) is an important control form and general utility tool of it. MAS can separate large, complex systems into small ones that can communicate and coordinate with each other and can be easy to manage. This paper starts from the concept and characteristics of MAS and microgrid, analyzes the wide range of MAS applications in micro-grid and its necessity. Then this paper focuses on the communication process of MAS in different scenarios (power restoration and power dispatch), and clearly demonstrates the convenience and practicality of MAS in MG applications. Finally, the paper looks forward to the application of MAS in MG, and believes that the emergence of 5G technology will greatly expand the application field of MAS.
Design of Ion Implantation and Deposition Signal Generator Based on FPGA and Touch Screen
Authors: Shu Weiquan , Zheng Yanhua
Published: February 2021

In order to improve the operation precision of ion implantation and deposition signal generator, to fix its arithmetic error and reach 1μs as the pulse adjustment unit, use FPGA and touch screen technology to improve the performance of signal generator. On the one hand, the FPGA board can directly affect the FPGA chip through Verilog to reduce the program operation time, on the other hand, replacing with crystal oscillator with higher frequency can make the program run faster and minimize the arithmetic error. The combination of FPGA and crystal oscillator can easily realize the clock input of MHz level and output pulse with 1μs as the adjustment unit, which has already been applied to signal generator as signal output source.
Computational Research and Implementation of Prediction of Pork Price Based on Deeplearning
Authors: Chen Taotao , Chen Zhongmin , Zhou Zhixuan
Published: February 2021

Social network public opinion has a wide range of social influence, which is one of the main external factors causing the fluctuation of pork market. However, previous studies have considered less factors outside the market, so the prediction accuracy is not high. A model based on LSTM about public opinion is proposed in this paper. Through multi-modal information fusion, the model makes use of the complementary advantages of multi-source information to enhance the estimated performance of the model. In addition, considering the influence of different fusion methods on the estimated performance of the model, six fusion methods are tried: Add, Sub, Max, Min, Con and AVG. For the sake of verify the effect of the model, the multimodal combination estimated model and the traditional regression model are used for comparative prediction. The results show that: in the task of pork price forecasting, the indicators of Multi_BERT_LSTM (CON) combined with Con mode are better than the contrast model, and the average absolute percentage error MAPE is increased by 17% compared with the optimal traditional forecasting model, and better prediction effect is achieved.