bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

AbstractIn 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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.