bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of a Narrow Transition Band Dynamic Digital Channelized Receiver withoutMerging Adjacent Sub-channels
Authors: Su Yu 
Published: April 2020

Abstract
In electronic reconnaissance, effective channelization of several input signals with unknown parameters is the key requirement of the broadband receiver. Generally, since the prototype filter must be perfect, the dynamic channelized receiver based on merging adjacent sub-channels to reconstruct non-uniform filter Banks occupies too many resources and is difficult to realize. This paper proposed a sharp wideband channelized receiver based on DFT filter banks and interpolated filter banks. The proposed receiver consists of an analysis section, channel detection and arbitration section, and a synthesis section. The analysis section divides the wideband signal into multiple sub-channels. Channel detection and arbitration section output the center frequencies and the bandwidths of the input signals. In the synthesis section, after being converted to baseband, the input signals are filtered and decimated to achieve the low rate signals. The proposed method released the design of the prototype filter from the requirement of perfect reconstruction. So it is computationally efficient. Besides, time-multiplexed and interpolated filter techniques can be used to further reduce the hardware complexity. Simulation results verify the validity of the proposed method.
Signal extraction based on chaos masking
Authors: Li Chao , Yu Jiayin , Guo Shiyu , Shi Mengna , Wang Erfu 
Published: April 2020

Abstract
As chaotic masking signal refers to a seemingly random and irregular signal occurring in a deterministic system, it is highly confidential to load the signal needed to be transmitted into chaotic masking signal as a carrier signal for transmission.In this paper, an improved information encryption based on lorenz chaotic masking system and speech signal extraction based on joint diagonalization blind extraction algorithm are designed.The performance comparison between the proposed algorithm and FastICA blind extraction algorithm based on negative entropy maximization is analyzed quantitatively and qualitatively in the simulation experiment. The effectiveness of information encryption under chaos masking and the reliability of the algorithm based on joint diagonalization blind extraction are verified.
Face Expression Recognition Based on Deep Learning
Authors: Zhang Tingxuan 
Published: April 2020

Abstract
Nowadays, the information technology such as artificial intelligence (AI) and the cloud classroom have been increasingly introduced to improve the quality of modern education. It is well known that teachers can adjust the teaching mode through the interactive performance of students in the classroom. For example, if many students show surprise expressions on their faces, it means that students may not understand what the teacher is talking about, and the teacher needs to slow down the rhythm and explain the knowledge point carefully. For another example, if students present positive expressions, it means that the teacher has mobilized the atmosphere of the classroom well and should keep this good teaching style to make students be interested in this subject. All in all, face expression recognition is quite useful in the modern society.
A Nonuniformity Correction Method Based on Gradient Scene Calibration
Authors: Liu Rang , Tong Yan , Ma Pufang , Zhao Yafei , Zhao Yanjie 
Published: April 2020

Abstract
The nonuniformity of infrared focal plane array (IRFPA) seriously affects the image quality and the measurement accuracy of the infrared imaging system. The two-point nonuniformity correction (NUC) method based on blackbody calibration performs a less than very satisfactory result to correct the sky scene with gradient gray distribution. Aiming at this problem, a new NUC method based on gradient scene calibration is proposed. First, the correction models are deduced in theory with the reference of the blackbody and the gradient scene. Then the pure sky images at the two different pitch angles are used as two reference temperature points to obtain the gain and offset coefficients by two-point correction. Next, two correction coefficients are filtered to remove residual noise. Finally, an outfield experiment with the proof-of-concept camera is performed. Experimental results show that the signal-to-noise ratio (SNR) of the point target image corrected by the proposed method is increased from 5.56 to 9.84 compared with the blackbody calibration-based NUC. And it has the preference of low complexity and easy implementation in the real-time system.
Research on Financial Development of Guangdong-Hong Kong-Macao Greater Bay Area Based on Endogenous Financial Economic Growth Model
Authors: Gao Houpu 
Published: April 2020

Abstract
Economic growth is a prerequisite for social development and political stability. Finance is the core and hub of modern economic operations and economic growth. GBA is an important strategy that the country is currently promoting. It is the region with the largest economic aggregate and the highest economic activity in China. Promoting the financial development of GBA has an important supporting role in enhancing the economy of the Bay Area and the national economy. Based on the strategy of GBA, this paper introduces the endogenous economic growth model of the financial sector to discuss the interaction and mutual restraint between financial development and economic growth in GBA.
RETRACTED: Research on Remote Control Method of English Multimedia Online Teaching System In Big Data Environment
Authors: Na Gao 
Published: April 2020

Abstract
In order to ensure the effectiveness and security of remote control of the teaching system, the remote control method of English multimedia online teaching system based on large data environment is proposed. Firstly, the remote control module of online teaching system is optimized, configuration parameters are improved, the remote control module is operated effectively, and the remote control rules of multimedia online teaching system are designed, which further ensures the security of remote control. According to the control rules, the remote control steps are simplified, and the optimization of remote control method for English multimedia online teaching system is finally realized. Finally, the experiment proves that the remote control method of English multimedia online teaching system in large data environment is more effective and safe than the traditional method.
Research on Home and Work Locations Based on Mobile Phone Data
Authors: Luo Xusen , Zhou Yunyao , Yang Yifu , Wu Shuyun 
Published: April 2020

Abstract
The home and work location information of residents is of great reference value for applications such as transport planning and urban development, since home and workplace are the most important places in people’s lives. The article introduces a method that uses mobile phone call detail records (CDR), which offers good potential for monitoring of the short-term mobility of populations, combined with city road network data, to identify respondents’ home and work locations. The method we developed contains three sections, which are data preprocessing, data fusion and location detection, and is tested with 6 months’ data collected in Hong Kong, including over 350 thousand residents. In the end, experiment results are compared with population register data and the results got in references, and it turns out that our method performs better with the average accuracy of 80%.
Design and Study UAV Data Link Terminal with One Station Controls Several Vehicles Dynamic Networking
Authors: Junkai MA , Wang Xiaoyan , Chen Kewei , Liu Qingtao 
Published: April 2020

Abstract
Considering that there are UAVdynamic networking and collaborative communication requirements under complex mission planning conditions, this paper designs a UAV data link communication terminal with One Station Controls Several Vehicles dynamic networking. Firstly, this paper analyzes the structure of One Station Controls Several Vehicles dynamic networking and cooperative communication system in UAV data link, and combines the characteristics of dynamic networking and task cooperative communication to design a One Station Controls Several Vehicles dynamic networking communication protocol stack and design the structure and function of the man-machine data link, the terminal device hardware is realized by the FPGA chip. This paper focuses on digital zero-IF signal processing unit design and hardware implementation process. Finally, combined with the terminal to build an indoor test environment, this paper tests the network function and performance. The test results prove that the UAV data link terminal in One Station Controls Several Vehicles dynamic networking is effective, and it is practical.
Probability Analysis of Ship Collision and Grounding in Inland Waterway Based on Big Data Analysis
Authors: Tang Yuheng , Mao Yuankang , Wu Mengjie , Shi Te , Fan Cunlong 
Published: April 2020

Abstract
With the rapid development of technology, mining valuable information from massive data has become an important part of the community. However, there are many deficiencies in the probability analysis of collision and grounding of ships in inland waterways, such as the insufficient use of data. The main purpose of this paper is to analyze the probability of collision and grounding of ships in inland waterways. Initially, big data analysis technology is used to preprocess the massive shipping data, and then the probability of the processed data is calculated by establishing the probability calculation model of collision and grounding. The results show that in the channel intersection area with poor shipping conditions, the increase of ship traffic volume will lead to the increase of ship collision probability; in the case of low visibility and long driving time, the probability of ship grounding will increase.
Short-Term Traffic Flow Prediction Methods: A Survey
Authors: Zhang Yijing 
Published: April 2020

Abstract
As a major part of a smart transport system, the vehicle management system has become an effective means for traffic management departments to control urban road traffic with the advent of smart transportation technology. The short-term traffic flow forecasting provides drivers with the best route as a core engineering of the car guidance system as well as the very relevant mathematical foundation in the field of intelligent transport, improving the traffic management schemes and managing traffic flow by measuring and projecting path flows. This paper mainly aims at incorporating the current mainstream approaches to avoid short-term traffic flow, including the ARIMA, RNN, Sparse Auto Encoder (SAE) and others. We hope that this article will help those who want to delve into it quickly.
Computer Finance Management System Innovation Thinking
Authors: Wu Guoqiang 
Published: April 2020

Abstract
With the rapid development of science and information technology, computer financial management has attracted the attention of enterprises. Computerization of enterprises refers to the use of computers to complete financial calculations, which can effectively reflect the operating conditions of enterprises. The socialist market economy system is gradually improving, and the scale of enterprises and market share are constantly increasing.Actively innovating computer financial management systems to gradually improve the efficiency of corporate computer financial management. Computer information technology plays a very important role in enterprise management, especially after the application of financial management system, computer financial management has a crucial impact on the operation and development of enterprises. This article is mainly aimed at the innovative thinking of computer financial management system, and puts forward opinions and suggestions based on the actual situation.
Review on Evaluation Criteria of Machine Learning Based on Big Data
Authors: Wu Hao , Jun Meng Fan 
Published: April 2020

Abstract
In machine learning in the context of big data, It is indispensable link for the evaluation results and indicators of prediction results. Although it is not as important as the core algorithm, it plays a role in related applications and research fields. The role of horizontal comparison of learning algorithms. The article briefly summarizes and reviews the research results of basic machine learning algorithm evaluation standards. Different evaluation methods are applied to different machine learning problems, and the trends and difficulties of machine learning evaluation methods in the future are analyzed.
Application Performance Prediction in the Datacenter to Accelerate Cloud Servers
Authors: Gao Gujia 
Published: April 2020

Abstract
Nowadays, cloud services become more and more important while datacenters are growing in scale. But the low effectiveness on cloud servers becomes an increasing issue as time goes. In this research, we focus on predicting application performance on cloud servers for acceleration. Linear regression and random forest are used in this study. Random foreset proves to be a precise, stable and effective tool to do performance counter prediction.
Personalized recommendations based on hotel online review data
Authors: Qin Haifei , Xu Wanjin , Zhao Yongchao , Wang Chunlin , Chen Xiaolin 
Published: April 2020

Abstract
With the development of network technology, independent travel is more and more popular. This paper constructs Hotel recommendations based on online review data. Firstly, we are starting from data acquisition, perceive and obtain the data that the online overview from the multi-agent-based on JADE. Secondly, we carry out semantic analysis of online comment data, according to the selecting, filtering, identifying, and merging data features, gain the feature of the hotel. Then, classifies online comment data and ranks hotels using combined feature words. Finally, we provide a personalized recommendation to users.
Research on the Identification of College Students’ Mental Health Problems Based on Campus Big Data
Authors: Ge Liang , She Yanyun , Jia Yu , Yuan Zhongwei 
Published: April 2020

Abstract
In recent years, according to the survey, college students have frequent mental health problems, such as anxiety, depression, inferiority, inter-personal sensitivity and other psychological problems, even the idea of suicide. It has a very serious negative impact on the family and society. If mental health problems of college students can be detected early, counselors can pay more attention to these high-risk students. At the same time, the high-risk students can receive therapies as soon as possible, reducing the harm. Therefore, it is crucial to find an effective method for early detection of mental health problems. This paper proposes a new method to detect mental health problems by analyzing students ’behavior on campus. The datasets include Internet access logs, records of entering and leaving dormitories, and records of consumption in canteens. We built classification models for differentiating the mental health problems of students from normal students. The experimental results show that the proposed method may be useful to improve the performance of public mental health services.
Container-Based Performance Isolation for Multi-Tenant SaaS Applications in Micro-Service Architecture
Authors: Wang Yu , Sun Yi , Lin Zhaowen , Min Jiangsong 
Published: April 2020

Abstract
With the development of cloud computing technology, SaaS has become a popular delivery mode in enterprise applications. Since multi-tenant can share a set of customized software applications deployed on the cloud, it significantly reduces the economic cost of providing software services of the cloud service provider. However, the sharing of cloud computing resources leads to service performance competition among tenants. Therefore, how to ensure that all tenants in the cloud have high-quality services becomes the most concerned issue for cloud service provider. To solve the above problem, our research aims at exploring an effective performance isolation mechanism based on container technology and micro-service architecture in multi-tenant scenario. This mechanism includes an SLA-oriented multi-tenant and multi-instance hybrid deployment scheme and a tenant performance isolation algorithm for microservice clusters, which can effectively reduce the performance competition among tenants, guarantee the SLA of tenants, and improve the cost-efficiency of cloud services. Experiments show that the request latency of the tenant working within their assigned quota can be reduced by 88.1% by applying the proposed performance isolation mechanism.
Distribution of scarce resources based on crowd density detection and queuing theory
Authors: Zhang Tingxuan 
Published: April 2020

Abstract
This paper makes a reasonable estimate of the number of charging stations to be set in each charging station by detecting the density of people near the charging station. Due to the shortcomings of traditional MCNNs that are currently commonly used for population density estimation, we added dilated convolution to the traditional MCNN and applied queuing theory to this problem. The population density estimation result of the MCNN incorporating the reduced convolution is used as the input of the aligned flow, so that the number of charging piles in each charging station is more reasonably set.
Serially concatenated extended CPM scheme based on TDRSS
Authors: Su Linbo , Wang Ningyan , Zhang Yani , Xia Guijin , Xue Yinghui , Lv Jiaoke 
Published: April 2020

Abstract
Tracking and Data Relay Satellite System (TDRSS) can meet the needs of Low EarthOrbit (LEO) satellite real-time transmission, but it also has large Doppler shift, transmission delay and channel fading. Continuous Phase Modulation (CPM), with excellent properties of both bandwidth and energy efficient, are very suitable for nonlinear and/or fading channels such as satellite channel due to the constant envelope nature. In this paper, the CPE in the SCCPM scheme is replaced by the designed ECE to construct a new scheme called SCECPM scheme, in order to enhance the robustness of the signal. Compared with previous SCCPM scheme, the proposed system shows an improvement concerning the convergence threshold and bit-error-rate (BER).
Analysis and Research on the Test Technology of Electric Vehicle Running Performance
Authors: Zheng Tuo 
Published: April 2020

Abstract
The gradual popularization and development of new energy electric vehicles brings not only opportunities but also challenges, such as new requirements for the technical analysis of running performance test. This paper first describes the evaluation index of the operation performance of electric vehicles, and then, based on the key index factors in the detection test of electric vehicles, analyzes the detection test technology and scheme of the operation performance of electric vehicles.
Research on Test Platform of Lithium Battery Management System based on LabVIEW
Authors: Luo Hao 
Published: April 2020

Abstract
With the application and popularization of new energy electric vehicles, the research and design of lithium battery management system is of great practical significance to ensure the normal operation of battery pack and vehicle safety, and improve vehicle performance. This paper first analyzes the design of the lithium battery management system, then designs the upper computer control system, and finally verifies the effectiveness of the lithium battery thermal management system through the system test.
Game Problem and Nash Equilibrium in the Electronic Payment Market with Multi-agent Participation
Authors: Xing Qiudan , Ma Jiahao 
Published: April 2020

Abstract
The rapid development of e-commerce has greatly promoted the popularization of electronic payment methods in China. The electronic payment service of online banking solves the problem of online transaction payment in the early stage of e-commerce development. After the rise of third-party Internet-guaranteed payment services, the problem of mutual trust in online shopping was solved in a breakthrough way, and the electronic payment service model was continuously innovated, and the electronic payment service scene was rapidly expanded and popularized. In this process, the relationship between third-party payment service providers and online banking has evolved from cooperation to competition, and has been developing in the contradiction between competition and cooperation. At the same time, the third-party payment model has brought great challenges to financial supervision. Based on the respective interests of the main participants in the electronic payment market, this paper applies game theory and its Nash equilibrium theory to analyze the optimal strategy choices of the participating entities in the electronic payment market, and gives their respective development strategies.
General model establishment and optimization dispatch of integrated energy system with power-to-gas
Authors: Ma Huan , Zhang Pengfei , Liu Zhe , Yang Yunwei , Li Jianqiang , Hu Xiaolong , Zhang Meixia , Yang Xiu 
Published: April 2020

Abstract
It is an important way to solve the problem of energy environment to use the new energy to run the multi-type energy coupling integrated energy system.Firstly, the mathematical model of power-to-gas (P2G) and electric-to-gas (P2HSS) energy storage system is established in this paper, and then the comprehensive energy system model of power-to-gas is established by using the modeling method of general energy hub. With the goal of reducing costs, reducing emissions, increasing new energy output and increasing P2G and P2H conversion benefits, optimization dispatch analysis was conducted. The numerical example shows that the consumption of new energy in the system is good. At the same time, P2HSS system has a significant effect on peak cutting and valley filling to ensure the economic and stable operation of the system.
The solution about primary frequency modulation of thermal power generating units is proposed based on the smart grid
Authors: Qing Yao Chang , Liu En Ren , Kun Pang Xiang , Kun Han Ying 
Published: April 2020

Abstract
The performance of primary frequency modulation of thermal power generating units taking part in power grid is good or bad which may bring a direct impact on the stability of the power grid frequency. The main problem from the function of primary frequency modulation about thermal power generating units is studied in this paper, and feasible rectification solution for the pressure in front of turbine and steady-state speed regulation is proposed, which provides some technical support for vigorously developing smart grid in our country.