bluuebunny/crossref_metadata_2025 huggingface dataset:
Frequency Diverse Array with Cubic Sinusoidal Frequency Offset
Authors: Qin Xinxin , Li Changli
Published: September 2020

Frequency diversity array radar (FDA) has range-angle dependent beampattern, providing enormous potential for the application of this new type of radar. However, the beampattern of conventional FDA (CFDA) has two problems: range-angle coupling and range periodicity, limiting the application of FDA. How to solve the problems is the premise of realizing beam accurate control and target accurate positioning. In this paper, we propose a new FDA transmitter structure with cubic sinusoidal frequency offset (Cubic sin-FDA). Simulation results show that this FDA beampattern eliminates coupling and forms a spot-shaped beampattern. Compared with the existing nonlinear frequency offset FDA beampattern, this method has a narrower half power bandwidth and lower side lobe level.
Invulnerability Analysis of Electric Power Optical Transmission Network in Smart Grid Based on Complex Networks
Authors: Shi Jianqiang , Sun Na , Xia Zhengyun
Published: September 2020

In order to improve the invulnerability of electric power optical transmission network in the smart grid, based on complex network theory, experimental simulation of random attacks and selective attacks on electric power optical transmission network in Jiangbei District of Nanjing City is carried out, and the method of improving the invulnerability of the network is given according to the simulation results. In the experiment of random attacks, we investigate the impact of single node failure on network connectivity and screen the hub nodes, and get the hub nodes that need to be protected. In selective attacks, two kinds of attack strategies are proposed, namely, network efficiency relative loss rate first attacks and real-time betweenness first attacks. From three aspects that include connectivity, network efficiency and network efficiency relative loss rate to evaluate the invulnerability of the network. The experimental results show that the electric power optical transmission network has the worst invulnerability to real-time betweenness first attacks. On this basis, an important node evaluation and protection method is proposed to improve the invulnerability of electric power optical transmission network, and the feasibility and effectiveness of the proposed method is verified by the example simulation.
Low-Latency Ultra-Wideband High-Speed Transmission Protocol Based on FPGA
Authors: Hu Jinxian , Wang Jinfeng , Li Rengang
Published: September 2020

Aiming at the shortcomings of current high-speed serial transmission protocol including high latency and low effective transmission bandwidth, this paper designs a low-latency, ultra-wideband high-speed serial transmission protocol based on FPGA. Based on homologous system clock, data scrambling and synchronous frame synthesis are used to complete the data integration, so as to increase the effective bandwidth of data transmission. The receiving end reduces the data transmission latency by using the internal logic of FPGA and the buffer pool built by the register group together with status machine. The protocol is simple and universal, which can be applied to the FPGA platform of any OEM. Experiments show that the protocol can effectively reduce data transmission latency, improve the effective bandwidth of data transmission, and monitor the health and error code status of each data transmission channel in real time.
Position and Speed Measuring Method of Maglev Train Based on Federal Kalman Filter and Information Fusion
Authors: Liu Chang , Cheng Shu , Li Kaidi
Published: September 2020

The position and speed measuring system is an important part of the High-speed maglev operation control system. The speed and position information accuracy and reliability directly affect the train operation safety. Aiming at the shortcomings and defects of the existing position and speed measuring methods, based on the Federated Kalman filter principle, a multi-source information fusion algorithm is designed to effectively integrate speed and position information from Inertial Navigation System, global satellite navigation system and Doppler radar sensor into the train position and speed measurement. On this basis, a combined position and speed measuring method for maglev train is proposed, it not only has high measurement accuracy, but also has strong robustness and autonomous operation ability. The effectiveness and reliability of the proposed method are experimentally verified based on the MATLAB software simulation platform. The experimental results show that the proposed method can be applied to the real-time position and speed measuring of high-speed maglev.
A Container Service Chain Placement Greedy Algorithm Based on Heuristic Information
Authors: Yue Qiang , Liu Xiangtao , Fang Lijia , Wang Xiaoxiao , Hu Wenbin
Published: September 2020

Container technology is a light weight back-end virtualization solution which copes with the growing demand for Internet service concurrency. Network services can be provided by a series of containers between which network requests are sent and responded. We call these cooperating containers a container service chain. On a certain physical cluster, there are various available container placement of a service chain. Different container placement causes different service response time. In order to reduce the response time of container service chain, a greedy algorithm for container service chain placement is proposed based on heuristic information. Through quantitative analyzing resources provided by hosts and consumed by containers, we build a mathematic model of container service chain. We use this model to decide where to place container when service is expanded, and where to remove container when service is reduced. Our model reduced the response time of container service chains by 40% compared to average placement.
Research on Monitoring Method of Impulse Vibration in Large Transformer Transportation
Authors: Zhang Zhengxiang , Zhou Haibin , Zhou Zhengchao
Published: September 2020

The safety of long-distance transportation of large power transformers has become an important constraint factor for the EHV projects. In view of the problems existing in the Three-dimensional impact recorders and condition monitoring system of the long-distance transportation of large power transformers, this paper analyzes the amplitude frequency characteristics and influencing factors of the impact vibration during the transportation of transformer, adopts the fast Fourier transform to deal with the interference in the vibration signal, designs a monitoring terminal of the impact vibration based on the Internet of things which can accurately measure the vibration impact of the transformer, and develops a remote real-time online monitoring system to monitor the displacement and impact of transformers at anytime and anywhere. The monitoring terminal and monitoring system are applied in the actual transportation of converter transformer in an UHVDC project. Three monitoring terminals are installed in different positions of the transformer to monitor the transformer status and send the monitored information to the monitoring system. The reliability of the terminal and the superiority of the monitoring system are verified.
Manipulations of Equivalent Preference in Parallel Allocation Mechanism
Authors: Huang Wei , Cai Dong , Huang Wen , Lu Yuge , Tang Qian , Huang Chong
Published: September 2020

The parallel distribution is a non-centralized mechanism for distributing indivisible items to agents, which can take into account computing efficiency, economic benefits and social equality. However, as most decentralized allocation mechanism, the parallel protocol is not strategy-proof. In this paper, supposed the manipulator has additive preferences with possible indifferences between single objects, we study the most basic manipulation problem under the parallel allocation mechanism. For any given set of items, we proved that the agent1 can determine whether all objects in the set can be guaranteed in polynomial time. In addition, we given an algorithm for finding pessimism and proved the correctness, completeness and time complexity of polynomial.
Intelligent Passenger-Flow-Control Scheme at Subway Stations in Smart City
Authors: Zhang Yuan , Li Congduan , Zhang Jinyang , Zhang Yiqian
Published: September 2020

With the rapid development of urbanization, more and more cities have built the subway systems. However, the super cities like Beijing, Shanghai and Guangzhou, have experienced problems such as overloading and insufficient capacity, especially during peak hours, due to the tremendous increase of passengers. A scientific and efficient optimization scheme is important to alleviate the passenger flow congestion problem and improve the transportation efficiency. This paper investigates the passenger-flow-control problem, aiming to shorten the average waiting time for passengers. An intelligent flow-control scheme is proposed to optimally alleviate the congestion problem in the subway system. Experiments show that the proposed flow-control scheme works well in alleviating the congestion and passengers’ waiting time at subway stations.
Interface Design Technology and Verification of Intelligent Manufacturing Oriented CNC System
Authors: Hui Shuangshuang , Yang Zhe
Published: September 2020

Objective With the proposal of German Industry 4.0, intelligent manufacturing has become the main direction of manufacturing technology development. In recent years, CNC technology industry for intelligent manufacturing has developed rapidly in China, and it has been widely used in various fields of manufacturing industry. Among them, the design of man-machine interface for system appearance is closely related to the operation mechanism of internal functions with high specialization and complexity, which has attracted more and more attention from the industry and designers. Therefore, the design method and key points of the human-machine interface of NC system will be discussed for intelligent manufacturing, and the technical verification will be made. Method The interface design requirements of intelligent manufacturing oriented CNC system were systematically analyzed, and the corresponding design techniques and key points were given. The specific design scheme and verification of Huazhong 9 interface design of Huazhong CNC were discussed based on a specific design case. Conclusion It is hoped that the design of man-machine interaction interface of intelligent manufacturing CNC system can be optimized and improved, and that a little contribution can be made to the CNC technology industry in China.
Computing the Subgame Perfect Nash Equilibriums in Parallel Allocation Indivisible Items
Authors: Huang Wei , Cai Dong , Lu Yuge , Huang Wen , Tang Qian , Li Youqiang
Published: September 2020

Multi-Agent resource allocation has also become a research hotspot in the field of artificial intelligence in recent years. A lot of related work aims to design a procedural resource allocation system with execution efficiency. This paper Studied a parallel allocation method for allocating indivisible items between agents in which every agent asks for an object among those that re-main in every round, and every reported item will be allocated randomly to an agent reporting it. In order to depicts the entire distribution process, the authors propose a method of constructing a game tree of parallel allocation. Study the corresponding relationship between the total number of branches of the game tree and items. In the last part, prof the parallel allocation mechanism is dynamic game and show that the subgame perfect Nash equilibrium (SPNE) can be found by backward introduction the game trees. Provides a method to compute the unique subgame perfect Nash equilibrium in linear time.
A Multi-hop Routing Mechanism Based on Local Competitive and Weighted Dijkstra Algorithm for Wireless Sensor Networks
Authors: Liu Qingwei , Liu Mandan
Published: September 2020

Extending the lifetime of the networks with limited energy has always been an important issue in the research of wireless sensor networks. Many researchers have contributed lots of routing techniques to improve energy efficiency and extend lifetime of the networks. In this paper, we proposed a Multi-hop Routing mechanism Based on local Competitive and Dijkstra algorithm (MRBCD). In MRBCD, CHs are elected by local competitive and CHs send data to the base station by their shortest energy cost path. By running local competitive mechanism, CHs in the network can be evenly distributed, which will balance energy consumption between sensor nodes. The inter-cluster routing mechanism can minimize the energy consumption in the inter-cluster communications. By combining the two mechanisms, MRBCD algorithm can balance energy consumption and improve energy efficiency, which will extend the lifetime of wireless sensor networks. Simulation results show that MRBCD algorithm extended the lifetime of the networks than LEACH and Multi-LEACH.
Performance Analysis of CSMA with Guard Channels in Heterogeneous Wireless Network
Authors: Jiang Jingyuan , Zhu Dongbi
Published: September 2020

We propose a CSMA scheme with guard channels in heterogeneous wireless network. In this system, there are two different networks B and A. Original users of A network (called network A users) can use the wireless resources of network A and B. Original users of B network (called network B users) can only use the wireless resources of network B. There are Ng
guard channels in network B, in order to guarantee the service quality of B network users. We model the system by three dimensional continuous time Markov chain and solve the steady state probability. We also obtain the system performance measures such as the total throughput, the loss probability of network A and network B users. Numerical results show that number of guard channels and the arrival rate of different network users give an important impact on the system performance, and the performance of our proposed CSMA scheme with guard channels is better than that of without guard channels.
Study on the Integrative Practice of University Teaching Space and Information Platform——Taking Xi’an Eurasia University as an Example
Authors: He Minjuan , Wu Lijuan , Sun Yu , Xu Yang
Published: September 2020

With the advancement of teaching reform in colleges and universities, the application of information technology in the teaching design and teaching process has become increasingly widespread. In addition to the applications of various software platforms and resources in the teaching process, more and more hardware-based smart classrooms and smart space are also being applied in the new round of teaching space transformation. What this thesis mainly studies is how to realize the integration of the universities’ teaching space and the teaching information platform, so as to further promote the reform and development of teaching mode. Based on the practical case of Xi’an Eurasia University, the study finds that in the process of teaching space transformation, informatization has enabled the connection between physical space and system platform, improving the efficiency and learning experience.
Evaluating Aspects of WeChat Use for Information Sharing During a Campus Attack Event Using Agent-Based Simulation
Authors: Beattie Steven , Xi Jing Yang (Sunny) , Chan Wai Kin (Victor)
Published: September 2020

Information sharing during emergency events often takes place through popular social messaging apps. An emergency response area of increasing concern in recent times is that of mass attacks on school campuses yet work studying information sharing systems in these situations is scarce. In this exploratory work, we used data from various sources to construct an agent-based simulation of a hypothetical knife attack on a university campus in southern China. We model the information sharing system after WeChat and evaluate the impact of group and individual messages on attack response and outcome. Evaluation metrics such as how students become alerted to the attack, the maintenance of accurate information, and casualty levels, are tracked. Results suggest that group messages may be most helpful despite being perceived as less trustworthy, and that the presence and structure of information sharing systems has a significant effect on response to campus attack events. Future work in the area is suggested.
DOA Estimation of Near-Field Broadband Signals Using Uniform Circular Arrays
Authors: Meng Zijian , Chen Haihua
Published: September 2020

This paper proposes a new approach of obtaining the direction-of-arrival (DOA) of near-field broadband signals using uniform circular array (UCA). Since the broadband signal source is located in the near field of the array, the signal received by the UCA can be modeled as a spherical wave. Take discrete Fourier Transform (DFT) of the received signal, we can get the frequency response of the received data. The frequency bins are then transformed to phase-mode signals by taking inverse discrete Fourier Transform (IDFT) of the signal in the spatial domain, which is used to estimate the DOAs of the received signals using multiple signal Classificaton (MUSIC). The covariance matrix of the received signal in phase-mode can be obtained by taking the average of the frequency bins. Furthermore, the proposed method has a characteristic of electronic steerability. Simulation results prove that the proposed near-field broadband DOA estimation algorithm not only has a better performance over the traditional methods, but also reduces the computational complexity effectively.
Research on Jamming to RF Screening Radar Based on Signal Reconstruction
Authors: Zhu Yuanjiang
Published: September 2020

Aiming at the problem that the jamming effect to RF screening radar by active jammer is not satisfactory, this paper provides one jamming method based on signal reconstruction. That jamming method conducts signal reconstruction based on estimation to radar signal parameters, which can achieve effective jamming to RF screening radar. The method at first, establishes jamming theory model based on signal reconstruction, and conducts simulation research accordingly. This paper makes simulation to that method. The results indicate that the relative intensity of main peak after pulse compression decreases with increase of frequency deviation or relative FM slope deviation, the decrease distribution caused by positive/negative deviation is symmetric, if frequency or FM slope of reconstructed jamming signal is closer to radar signal, the gain is higher after pulse compression. So overall consideration should be conducted during jamming design to select proper frequency deviation and FM slope according to jamming power. The method provided in this paper has important reference value for engineering research.
Cannon: A Pocket Laboratory for the Experiment of Short-Range Wireless Communication Course
Authors: Yang Kai , Li Jiayan
Published: September 2020

The widespread use of short-range wireless communication technology in many areas requires students who major in electronic engineering to have a basic understanding of the technology. Therefore, there is a necessity to strengthen experimental teaching in short-range wireless communication course. This paper presents a pocket laboratory named Cannon for the above course, which will be taught at the second or third semester of the department of electronic engineering in Changzhou Institute of Information Technology. Cannon is used to introduce to students the basic application implementation methods of Bluetooth Low Energy (BLE) communication practically. Cannon not only contains a complete Bluetooth intelligent hardware system, but also has its own JUMA SDK, a BLE application development framework developed by JUMA Technology. The feedback from students shows that Cannon can make their learning process faster and encourage them to acquire the skills necessary to accomplish the BLE application.
Dilated Denoising U-Net Network Improving the Adversarial Robustness
Authors: Zhang Xianshan , Jia Fan
Published: September 2020

The adversarial attack generates adversarial samples by adding subtle perturbations to the image. Such perturbations are usually very small and undetectable, but the neural network will give completely different results from the real sample. Adversarial example completely fools the neural network. Therefore, it is very important to develop effective defending model. Convolutional neural networks have successfully achieved adversarial robustness by removing noise in adversarial samples. However, the convolutional neural network involves multiple layers, and the denoising model contains a large number of parameters. This paper proposes a dilated convolutional denoising U-Net network to remove adversarial sample noise. Compared with the previously proposed denoising U-Net, our model has fewer layers. Dilated convolution is used in the convolutional layer to expand the receptive field. Use zero padding to ensure that the output dimensions are consistent with the input dimensions We conducted experiments on the ImageNet dataset. The experiments show that the extended of the receptive field can enhance the ability of the U-Net network to capture detailed image information, enhance denoising performance, and effectively improve the robustness at a lower computing cost.
Prototype of Data Link Based on Random Modulation Hopping and Automatic Modulation Recognition
Authors: Wang Yiwen , Liu Chunhui
Published: September 2020

A model of data link system based on modulation hopping and Automatic Modulation Recognition (AMR) is proposed, and the prototype of the pro-posed system is developed with GNU radio platform and the universal software radio peripheral (USRP). At the transmitting end of the prototype, the random sequence is generated to control modulation hopping pattern. At the receiver part, an AMR Network module recognizes the modulation mode and sends the information to the demodulation module to obtain the data flow. In the experiment, the speed of modulation recognition and the tracking ability of the modulation hopping under typical working environments are verified and analysed. The experimental results and the analysis of the corresponding parameters verify the rationality and availability of the system design.
Research on Transmission Performance of Double Leakage Cable Based on LTE-M System under Tunnel Simulation Environment
Authors: Liu Bo
Published: September 2020

With the improvement and maturity of LTE technology, the vehicle-ground wireless communication system based on it has become a new technical direction of rail-vehicle-ground communication in recent years. Based on an LTE-M vehicle-to-ground wireless communication system covered by double leaky cables, load simulation service tests were carried out to test the transmission performance of leakage coaxial cables. This study found out that when two leakage cables are HV: one is horizontally polarized and another vertically polarized, the average transmission rate of the vehicle-ground communication system of the same polarization mode increased by about 50%. At the same time, there was no significant decrease with the system transmission rate when the space between them reduced from 1 m to 0.3 m. Thus, an optimized leakage cable deployment scheme was obtained. When the horizontally polarized and vertically polarized leakage cable was used and the space between the two leakage cables was 0.3 m, the optimum transmission rate has been achieved.
LRERNet: Low Resolution Expression Recognition Network
Authors: Ma Yipeng , Tong Feifei , Wang Yuehai
Published: September 2020

Facial expression recognition (FER) is a meaningful but challenging research direction. An important reason is that the image resolution used for FER is usually low. At present, there is no specially designed model for the challenge of low resolution FER. We propose a low resolution expression recognition network with front and back end structure using specially designed dilated convolution groups. In addition, for the need of pension agency, we establish a dataset for studying FER of the old in Asian countries and we named it AOPFE. We evaluate our method on three standard datasets (RAF, SFEW and CK+) and AOPFE. In our experiments, the method achieved good results in these datasets especially on RAF dataset.
A Dynamic Channel Selection Algorithm of Data Forwarding in Wireless Mesh Networks
Authors: Yang Jianjun , Shen Ju , Guo Ping
Published: September 2020

Wireless Mesh Networks (WMNs) is an emerging technology in networking, in which the devices (nodes) are configured with multi-radios, making the overall capacity improved significantly. Nodes avoid interference with each other by tuning to different channels of the spectrum space. When a node intends to communicate to other nodes, especially a node far away from it with multiple hops, it is critical to find the channel with largest bandwidth to forward the packet. A dynamic channel selection algorithm is presented in this article, by which each node is able to find its next hop based on the criteria of possible largest channel bandwidth to carry out the forwarding. The novel idea of our approach is that only three past numerical data are kept by each node, and then it is able to calculate the potential bandwidth capacity and continue the most efficient forwarding. Simulations experiments were conducted and the results demonstrated that our mechanism outperforms peer approaches in terms of bandwidth capabilities and delay in Wireless Mesh Networks.
A Deep Convolutional Learning Method for Blind Recognition of Channel Codes
Authors: Tian Feng , Wang Jiao , Li Jianqing
Published: September 2020

Blind identification of channel codes is a significant part in the field of non-cooperative signal processing. It plays a significant role in intelligent communication, information interception, information confrontation and so on. To solve issues of high dependence of manual extraction of expert features, low robustness, difficulty of deployment from traditional methods for blind recognition of channel codes, this paper presents a novel way for blind recognition of channel codes by integrating deep learning technology. For the extraction of features from signals, deep convolutional neural network containing 4 convolutional layers is designed. For model training, database of convolutional codes is generated. Experimental results show that this method can achieve 98%+ recognition accuracy with SNR not lower than 4 dB, which proves the effectiveness of the method.
A Power-Efficient and Secure Communication Scheme in Satellite Communication
Authors: Zhao Shengli , Lan Xianliang , Yu Zihan
Published: September 2020

Resource is very limited in satellite communications, thus issues on security and power-efficiency in satellite communications have aroused extensive attention in recent years. In this paper, we have proposed a transmission scheme in satellite communication systems, which is secure and power-efficient. The binary bit sequence is encrypted prior to the modulation step, thus achieving security. The security analysis is based upon the Wyner wiretap model. In the wiretap model, the transmitter attempts to send messages to the legitimate receiver, meanwhile the eavesdropper is passively wiretapping. The legitimate receiver is assumed to have a good knowledge of the secret keys, so he can recover the original signal. However, the eavesdropper experiences severe interference and cannot mitigate it. The secrecy performance is measured by the secrecy rate. The secrecy rate is the rate difference between the legitimate communication and the illegal communication. Security of the proposed scheme is demonstrated by the mathematical analysis and Monte-Carlo simulations. In addition, the key space and the time needed to crack the secret keys are also calculated. The analysis results illustrate that the proposed scheme can provide a substantial security enhancement to the satellite communication system, meanwhile achieves power-efficiency.
Remote Sensing Scene Classification Based on Improved GhostNet
Authors: Wei Biyun , Shen Xiaole , Yuan Yule
Published: September 2020

Nowadays, the design of convolutional neural network (CNN) models is getting deeper and wider. When traditional CNN is used to process limited data of remote sensing images, it will lead to overfitting. We will use lightweight and efficient models to classify remote sensing images. In order to improve the classification accuracy and reduce the intermediate parameters, we improved GhostNet and proposed a smaller CNN named Improved GhostNet. Meanwhile, we use image enhancement methods to enlarge the datasets and dropout, it will reduce the amount of parameters. We experimented on three datasets, such as AID, UC Merced, NWPU-RESISC45. Then, we used MobileNetV3-Small and GhostNet to compare with our CNN model. The classification accuracy of improved GhostNet achieves more than 91%, and the accuracy on the AID is improved by 2.05% compared to the original GhostNet. These results demonstrate the effectiveness and efficiency of improved GhostNet.
Research on Population Distribution Model Based on Communication Base Station—Take Shanxi Province as An Example
Authors: Yang Bin
Published: September 2020

The goal of earthquake prevention and disaster reduction is to scientifically manage the risk of earthquake disasters in order to reduce the impact of earthquake disasters on social economy. The main goal is to reduce casualties. Accurate information of population distribution is an important prerequisite to reduce the impact of natural disasters on population. At present, the population data in the provincial earthquake emergency database are mainly statistical data, which can be divided into population data based on administrative division and population data based on kilometer grid. The population gridded data is closer to the actual distribution of the population than the traditional census statistics, but it is also mainly based on static data. Neither can reflect the changes in the distribution of people during the day, nor can it reflect the impact of holidays on the flow of people, so it is very important to study the dynamic population distribution data. This paper analyzes the main methods of the existing population distribution model, compares the advantages and disadvantages of each model, and points out the limitations of the static population distribution model. At the same time, based on the communication base station and based on the population distribution model of the residential area, Shanxi Province’s work day/holiday population distribution model was established. And through data comparison and analysis, the feasibility of this method is verified.
A Three-Step Strategy for Recommendation in Mobile Police Video Secure Access
Authors: Yin Xinming , Guo Yi , Cao Zhiwei , Xiong Min
Published: September 2020

Mobile police video security access link is an important boundary channel to ensure the secure and trusted access of mobile video in the private video network. Therefore, this paper proposes a three-step strategy for access control, encrypted transmission, and wireless video security inspection. While carrying the ability to carry higher video streams, it is both safe and reliable, and has strong scalability in performance. This paper analyzes the access mechanism of SSL VPN in encryption, identity authentication and resource access control. Proposes a mobile police video security access link solution based on SSL VPN for network clients. Respectively presents a secure access solution for wired video and wireless video. And a load balancing access scheme based on NAT address translation is designed. Finally, a test scenario for the maximum number of concurrent users and server bandwidth performance is designed, implemented and analyzed. In actual application, the trial projects have been highly recognized by public security customers.
Research on Typical Architecture and Application of Distribution Internet of Things Based on Blockchain
Authors: Sun Yue , Yang Jiaxuan , Chen Wei , Xu Xiaotian , Gong Gangjun
Published: September 2020

The new round of energy reform is marked by large-scale development and utilization of new energy and re-electrification as the fundamental path, to cope with the pressure of absorbing renewable energy and stupendous access to variable loads such as electric vehicle charging piles creates several problems such as a large number of equipment failure and low standardization in the distribution network, to overcome this, the distribution Internet of Things (D-IoT) came into existence. In this paper an equivalent architecture of blockchain and D-IoT is built based on master-slave multi-chain. The combined equivalent architecture proposes the crucial application of blockchain technologies as consensus mechanism and smart contract in the D-IoT in order to explore the broad application prospects of blockchain in the D-IoT.
Security Protection Scheme of Brain-Like System Based on Cloud Computing Platform
Authors: Wei Haoyu , Xiao Nanfeng
Published: September 2020

The functions of human being’s brains are very difficult to simulation by computers, therefore many scientists are focusing on research of brain-like system (or robotic brain) based on cloud computing platform, which can simulate the human being’s hearing, vision, thinking and action. However, due to the security incidents of the internet occur frequently, the robotic brain based on the cloud computing platform may be seriously harmed by the security incidents. Therefore, this paper designs and implements of the overall security solution of the robotic brain based on cloud platform. The cloud platform intranet is divided into the intranet trusted zone and the DMZ zone, and strict filtering strategies are set in the zone, and firewalls and firewalls are set up in the DMZ zone and the external network zone. Monitor incoming network traffic at the network interface, and deal with abnormal traffic. At the same time, it audits security events in the intranet, conducts the statistical analysis on content security, server security, and application control, and blocks suspicious attacking IP. A series of safety measures are adopted to ensure the safety of the internal network of the robotic brain based on cloud platform.
Evaluation on the Effect of High-Level Scientific and Technological Talents Team Building in Local Industry Based on DEA
Authors: Wang Fenglian , Zhou Xiaohong
Published: September 2020

In recent years, the attraction and investment of high-level scientific and technological talent team in local industries have been increasing. But how to evaluate the effect of team building is a challenging problem in the development of local industries. This paper establishes a DEA model in which human and financial resources are input, knowledge output, economic benefit and social benefit are output, based on DEA method, combining the characteristics of local industry development and the current situation of high-level scientific and technological talent team. And then, this paper evaluates the construction effect in the past five years and clarifies the shortage of professional and technological talents in W City, clarifies the problems of insufficient professional and technical personnel, insufficient professional team strength and low concentration of regional innovation and entrepreneurship in this city, and puts forward corresponding countermeasures. The purpose of this paper is to provide theoretical ideas for the evaluation of the effect of high-level scientific and technological talents team building in local industries.
Application Research of Data Analysis and Mathematical Model Prediction in Marine Fishery
Authors: Si Yingqian , Huang Ziling , Wu Ruoxi
Published: September 2020

Fishery resources are the biological resources which are constantly updated and changed, Global ocean temperature affects the habitat quality of some marine organisms. When the temperature changes too much to continue to live, these organisms begin to migrate to more suitable places. If fishery companies can understand the migration regular of fish when the ocean temperature changes in advance, it will improve the efficiency of fishing. On the basis of previous project research, this paper studies the influence of sea water temperature change on the migration of herring and mackerel in the North Atlantic of Scotland, and establishes a prediction model of sea temperature. The model predicts the temperature of the Western Ocean in different latitudes near Scotland in the next 50 years, so as to predict the migration direction and migration frequency of the two kinds of fish. Through time series regression analysis, the shortest, longest and average time for the two kinds of fish to leave Scotland were analyzed and the migration direction and frequency of these two species were predicted, which can provide a reference for small-scale fishery companies in the coastal area of Scotland to solve the problem of declining fishing rate due to migration of herring and Mackerel. The conclusion and method of this study can also provide reference for other similar cases.
Zero Determinant Strategy to Enhance Environmental Protection Cooperation of Enterprises
Authors: Tang Yuan , Huang Yuanyuan
Published: September 2020

Industrial enterprises are the main source of environmental pollution in our country, which has caused great damage to the ecological environment. The government has been paying more attention to environmental protection, but previous studies have focused on the one-way influence of the government on industrial enterprises, ignoring the two-way relationship between the government and industrial enterprises, and the interaction between enterprises and enterprises. Enterprise is designed to maximize their own interests, which damages system performance. In this paper, we simulate the interaction between government and enterprises, enterprises and enterprises as a repeated game to guide enterprises in their efforts to reduce pollution. We apply a zero determinant (ZD) strategy for the government and enterprises. No matter what their opponents do, they are able to defend their interests with their ideal values and find the conditions for their best. Numerical results demonstrate the performance of the two zero determinant strategies that are recommended.
Research on the Quality Supervision System of Agricultural Product Based on Big Data
Authors: Zeng Yitang
Published: September 2020

The issue of agricultural product safety is important for the economy and the people’s living in our country. It is necessary to build a quality supervision system to strengthen the quality supervision and improve the quality for agricultural products. This paper systematically analyzes the role of big data in the quality supervision system of agricultural products and its innovative driving mechanism for operation mode. It contains the design of the construction of quality supervision system for agricultural products based on big data and the quality supervision of agricultural products operation mode. It proposes measures to strengthen the construction of quality supervision system of agricultural product based on big data.
Research on the Integration Construction and Operation of Regional Ecological Industry and Modern Service Industry under the Background of Big Data
Authors: Sui Zhichun
Published: September 2020

Based on the analysis of the current situation of the development of regional ecological industry and modern service industry, the data of regional ecological industry and modern service industry are extracted, the statistical index system based on the integration of the two big data tools is established, the big data tools are used to extract the large amount of data, and the relevant mathematical models of big data are used to analyze and predict the regional ecological industry and modern service industry, according to the calculation results. By analyzing the reasons, we can improve the strategy of the integration of ecological industry and modern service industry in the whole region, make it run effectively, and promote the overall development of the whole national economy.
Enlightenment on Vocal Music Classroom Teaching from the Perspective of Big Data
Authors: Zhang Yongfang , Li Haoran , Ye Peijie
Published: September 2020

With the arrival of the era of big data, mobile Internet, Internet of things, cloud computing, etc. are constantly changing our lives. The high-speed development of information technology is boosting the development of educational information, restructuring our classroom teaching and learning methods, which of course also includes vocal classroom teaching. This paper briefly introduces the relationship between the era of big data and vocal music classroom teaching, analyzes the factors affecting vocal music classroom teaching from the big data, and studies the new ideas of vocal music classroom teaching from the application of information technology. At the same time, this study also describes the role of information technology-based “singing situation” teaching in vocal music teaching, such as skill training, voice image shaping, blending scenes, etc., to guide students to apply the emotional characteristics of singing thinking to singing art activities, and strive to provide some new enlightenment for the current vocal music classroom teaching through the power of scientific and technological information. It also provides theoretical basis for the innovation and reform of vocal music classroom teaching.
Communication Security Design of Brain-Like System Based on Cloud Computing Platform
Authors: Deng Gang , Xiao Nanfeng
Published: September 2020

This paper mainly studies the communication security problems of brain-like system (or robotic brain) based on cloud computing platform, and designs a more convenient and safer communication mechanism for the robotic brain, which includes password algorithm design, digital signature design before login, data exchange design during login process, and security protection design against network attacks. Only the legitimate users can communicate with the robotic brain to ensure that the control authority of the robotic brain is not illegally stolen. In the authentication process, the key agreement must be carried out first, the user name and password of the legitimate user must be encrypted and sent, and the encryption algorithm must be guaranteed to be unable to be deciphered under the existing technical conditions. For the important communication data, the encrypted transmission is required, the encryption key is determined through negotiation, the encryption algorithm must be safe and reliable, and the encryption and decryption speed must be guaranteed. This process requires ensuring that communication data is not stolen illegally, and the data can be verified to avoid tampering and illegal data insertion. The users may control the robotic brain to work, and ensure its safety during the communication process.
Research on the Influence of Cultural Creativity Industries on Regional Economic Development in China Based on Moderating Effects
Authors: Fang Liang
Published: September 2020

Cultural creativity industries are new driving force of regional economic development. Based on 10 specific evaluation index systems, this paper constructs cultural creativity industries variable, and uses factor analysis, multiple linear regression and hierarchical regression analysis to analyze 31 provinces (municipalities and autonomous regions) in China. The research shows that: cultural creativity industries have a significant role in promoting regional economic development, economic environment has a positive role in moderating effects, the better economic environment, the more obvious role of regional cultural creativity industries in promoting regional economic development, cultural creativity industries and educational environment have a positive role in promoting regional economic development, education environment has a positive moderating effects, science-technological environment has a positive moderating effects, and the better regional science-technological environment is more conducive to the promotion of cultural creativity industries to regional economic development.
Application and Development Prospect of Artificial Intelligence and Big Data in Medical and Health Field
Authors: Zhang Yunyan , Ding Xingfeng , Hu Feng
Published: September 2020

Artificial intelligence and big data technology have broad development prospects in the medical field. This article introduces the development of artificial intelligence and big data process, artificial intelligence and big data technology mainly in the field of medical health development condition, artificial intelligence and big data applications in healthcare, artificial intelligence and big data exist in the field of medical health challenges shows the four aspects of artificial intelligence and big data technology is widely used in the field of medical, think that artificial intelligence and big data promoting and deepening health reform, but also faces some obstacles in the development. In order to develop the supporting ability of intelligent medical treatment, some Suggestions are put forward, such as the combination of technology and products, demand, data exchange acquisition ability, interpretability of results and improvement of laws and regulations.
Research and Application of Integration Solution for Enterprise-Level Heterogeneous Document Management Systems
Authors: Huang Shujun , Meng Xiangsheng
Published: September 2020

This paper proposes an enterprise-level document management system integration solution, which can effectively solve the problems of the coexistence of multiple document management systems in enterprises and public institutions, the repeated collection of document data and the inefficient access application. The solution also can effectively support the data security and confidentiality of enterprises and public institutions. The core idea of the integration solution is to realize the application integration between the document integration application system and the document information management systems by taking the document classification collection management regulations as the management basis, taking the document information integration application system as the technical carrier, and adopting the SOA technology. The integration solution has been proved to be effective in practice, with significant application value and promotion value.
Research on the Reference of South Korea’s Science and Technology Industry Innovation Cluster Development to Macao
Authors: Shao Bo , Li Ruo-Ran
Published: September 2020

As an advanced form of Innovation Cluster after the Fourth Industrial Revolution, Scientific and Technological Industrial Innovation Cluster has become an important support to promote the development of national innovation in the future, and the world’s advanced countries have optimized the development of Traditional Innovation Cluster according to it. This research introduces the development needs of Macao’s Traditional Innovation Clusters through its innovation capability and innovation index, compares the advantages and disadvantages of Innovation Clusters and Industrial Clusters, and discusses the future development mode of Macao’s technological innovation by learning experience from the development of South Korea’s Science and Technological Industrial Clusters. According to South Korea’s experience and the advantages and characteristics of Macao’s regions, the construction should be reformed based on the advantages of Industrial Clusters and regional development so as to reduce costs and control the scale of investment. At the same time, it’s also vital to actively develop and utilize Hengqin New District, attract top scientific research institutions and talents from the world, in which way Macao’s Science and Technology Industry Innovation Cluster could be built.