bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of physicochemical properties on band gap energy and glass transition temperature of (GeS2)10(Sb2S3)90−x(AgI)x chalcohalide glasses for Near-IR applications
Authors: Boukhris Imed , Hegazy H H 
Published: January 2021

Abstract
The dependence of band gap energy (Eg) and glass-transition temperature (Tg) on physico-chemical properties for the (GeS2)10(Sb2S3)90−x(AgI)x (10 ≤ x ≤ 50 at%) chalcohalide glasses were theoretically investigated. Chalcohalide glasses have wide technological applications owing to the aptitude of tuning their optical band gap through composition change. Therefore, Eg of the studied chalcohalide glasses was estimated using different methods, and it was turned out that it decreased as the AgI amount increases. This decrease was elucidated in terms of physico-chemical properties. In addition, we determined the positions of conduction band (ECB) and valence band (EVB) by using the computed values of Eg. The density and molar volume increased while the packing density decreased by adding AgI. The overall coordination number (CN), crosslinking density (CD), constraints number (Ns), cohesive energy (CE), heat of atomization (Hs) and overall mean bonds energy (〈E〉); computed via the chemical bond approach (CBA); decreased with the increment of AgI amount. In contrary, the floppy (F) and mean bonds energy (Es) increased. Finally, two estimations of Tg were presented based on 〈E〉 and CN. The two estimations showed a decreasing trend when adding AgI content.
An Advanced Fourier Descriptor Based on Centroid Contour Distances
Authors: Nan Liao Nan , Guo Baolong , Li Zekun , Zheng Yan 
Published: January 2021

Abstract
In order to distinguish two shapes with similar centroid contour distances. This paper proposes a novel descriptor-AFD-CCD (advanced Fourier descriptor based on centroid contour distances), which is based on FD-CCD ( Fourier descriptor based on centroid contour distance ) descriptor. FD-CCD only provides the distance information from the centroid point to the contour point, and the lack of direction information affects the accuracy of matching. The algorithm uses circularity and rectangularity to supplement discriminability, with low computational complexity. Tests were performed on three datasets. The experimental results show that AFD-CCD has further improved the matching accuracy while ensuring that the matching speed does not decrease.
Investigation of real-time optimization based on CAN bus
Authors: Du Feng , Cai Yijie , Guan Zhiwei , Tang Fengmin , Wu Di , Shi Heping , Wang Tong 
Published: January 2021

Abstract
Aiming at the problem of CAN bus network transmission delay which affects the transmission rate, a bus network transmission delay model is established. The main indicators of network transmission delay are modeled. A hybrid optimization combining message offset compensation and identifier optimization is proposed. In terms of overall optimization, an optimization method for message segmentation and encoding scheme is designed, and a method for offset compensation of delayed messages is designed for partial parts. Symtavision software is used to simulate network conditions of the two CAN buses. Analyse the main indicators of delay after the optimization plan is adopted. The simulation results show that the hybrid optimization scheme can reduce the delay by more than 16% compared with before, which significantly improves the network communication quality, and improves the network transmission rate and scalability.
Prediction of Sea Clutter Based on Recurrent Neural Network
Authors: Wang Wenyuan , Ji Tingting , Sun Jinghao 
Published: January 2021

Abstract
As radar sea clutter has chaotic characteristics, a prediction model can be established to predict sea clutter according to short-term predictability of chaotic time series. Therefore, this paper proposes a sea clutter amplitude prediction model based on LSTM, Stacked LSTM and Nested LSTM. This paper first obtains the best state space for sea clutter prediction according to the phase space reconstruction theory and establishes the prediction equation, then uses three networks to predict the sea clutter amplitude, and finally compares the effects of the three neural networks and analyzes the factors that affect the prediction precision. The experimental results on the IPIX radar data and P-band radar data show that, the model used in this paper has a smaller prediction error than RBF, and the prediction performance is better. The model can achieve high-precision and high-efficiency prediction of sea clutter and has verified the effectiveness of the method.
Analysis of Equipment Anti-interference Problem in Electronic Information Communication Engineering
Authors: Xie Yang , Qiu Xiuling 
Published: January 2021

Abstract
This article analyzes the role of equipment anti-interference in electronic information and communication engineering. This paper studies how to improve equipment operating efficiency, reduce the probability of leakage problems, and improve the quality of information transmission. Combining the principle of equipment anti-interference in electronic information and communication engineering, the author studies the related causes of equipment anti-interference problems, how to deal with transmission interference problems, how to deal with external environment and receiving interference problems. In addition, the author also proposed preventive measures against the above problems and countermeasures for the integration of technical work. The purpose of this article is to improve the operational stability of electronic information and communication engineering equipment and improve the anti-interference ability of the equipment.
Co-frequency signal interference detection based on multiple antennas and multiple channels
Authors: Shuai Jianli , Wang Zuo , Yang Peng 
Published: January 2021

Abstract
Co-frequency signal interference detection plays an absolute role in eliminating same-frequency interference. Eliminating same-frequency interference can improve signal-to-noise ratio and reduce communication errors. For an uncoded multi-antenna multi-channel system with Ni
transmitting antennas and Nj
receiving antennas, the algorithm is optimized on the basis of the QRD-M algorithm, and a depth-first QRD-M algorithm based on single-layer ML (ML-1 -IQRM algorithm), compared the performance of the ML-1-IQRM algorithm with the original QRD-M algorithm. The experimental results show that the ML-1-IQRM algorithm can better detect the interference of the same frequency signal.
Electromagnetic Mutual Inductance Coupling Model of Wireless Power Transfer in Oil-gas downhole
Authors: Wang Yuelong , Ding Yingzhi , Bi Lingzhi , Yang JingYi , Li Yizhen 
Published: January 2021

Abstract
According to the wireless power transfer system (WPT) in oil-gas downhole, the structure of the WPT device suitable for the simultaneous existence of oil-water medium in high-temperature and high-pressure environment is put forward by using the principle of electromagnetic induction. Through the analysis of magnetic circuit, the electromagnetic mutual inductance coupling model is established, and the main factors affecting the transmission efficiency are obtained. Based on the model, the system is simulated and verified by experiments, in order to further improve the efficiency of power transfer system.
Underwater magnetic target signal denoising based on modified wavelet decomposition and reconstruction algorithm
Authors: Qin Tao , Cao pingjun , Zhang yuzhu , Liu zhanxin , Chen zhengxiang , Zhang xuebin , Dou Ke , Dong Hao 
Published: January 2021

Abstract
Noise reduction is crucial for magnetic anomaly signal detection of underwater ferromagnetic target. Modified wavelet decomposition and reconstruction algorithm is proposed to suppress the colored noise and improve the signal to noise ratio. Hamming window is employed to make the preprocessed signal continuous. Evaluation index based on signal-to-noise ratio function is selected, wavelet decomposition and reconstruction algorithm iterates adaptively to select the optimal order of decomposition and reconstruction. The experiment result emphasizes that the signal-to-noise ratio of novel algorithm is 71.6dB. In this particle, we provide a new method to improve signal-to-noise ratio and enhance real-time signal processing for underwater target magnetic anomaly signal detection.
The Design and Investigation of Space Photovoltaic Array Hardware-simulator
Authors: Wang Shuang , Zhang Xiaoming , Gao Xinyu , Tian Yun , He Jing , Liang Quan , Tian Dong , Zhao Ting 
Published: January 2021

Abstract
A hardware part of space photovoltaic array simulation system is designed in this paper, to realize the actual output characteristics of photovoltaic array. In this paper, the design of a PV array emulator (PVAE) is presented. By analyzing the V-I characteristic curve of solar cell given by the previous software, the simulation scheme is developed. Secondly, the control scheme of the proposed emulator based on DC-DC converter is discussed in detail, than the transfer function of the whole system is established, at last the digital controller based on DSP is designed. A prototype 200W PVAE based on full bridge DC-DC converter has been made, the experimental results show the validity of the controller design. The application of the PVAE can greatly shorten the research and design cycle of photovoltaic array power supply system of spacecraft, improve the research efficiency and credibility of research results.
Identifying Influential Nodes in Complex Networks Based on Local and Global Methods
Authors: Mijia Li , Hongquan Wei , Yingle Li , Shuxin Liu 
Published: January 2021

Abstract
Identifying Influential Nodes in complex networks is of great significance in both theory and reality. K-shell decomposition method is a local method which is suitable for increasing scale of complex networks but limited in accuracy because many nodes are partitioned with the same K-shell value. To overcome the coarse result of K-shell, an improved K-shell which considers the number of nodes’ iteration layers and degrees is proposed. Unlike local methods, global methods such as Betweenness Centralities (BC) are accurate but time-consuming. We employed an algorithm framework which combines advantages of both local and global methods where core network is extracted by improved K-shell and then BC is used to quantitatively analyze nodes in the core network. We compare the proposed method with other existing methods on Susceptible-Infective-Removal (SIR) mode. Experiments on three real networks show that the proposed method is more efficient and accurate.
Research on laser Link performance of UAV-based platform based on reverse modulation
Authors: Yang Bo , Huang Guoce , Wang Yequn , Wang Guisheng 
Published: January 2021

Abstract
In order to solve the problem of UAV-based optical communication under the constraints of low load, high transmission rate and low bit error rate, this paper studies the alternative scheme and the possibility of optical communication system based on reverse modulation. Based on the study of atmospheric effect, alignment error, and reverse modulator performance, the light intensity propagation model is constructed. Through MATLAB simulation, it is found that under weak turbulence, the link communication distance can reach 7-12km.Good communication effect when turbulence intensity is below 0.4; Increasing the receiver size can improve the communication chain performance effectively.
The networking performance analysis of wireless broadband communication in electricity system
Authors: Tang Xiaoke , Wang Rui , Wang Yubo , Zhao Dongyan , Zhao Xu , Zhang Yubing 
Published: January 2021

Abstract
HPLC (high speed power line carrier) is widely used in electricity information collection, but because of the large variation of attenuation of power line channel, in some environment, it needs wireless communication as supplement router, the current wireless technology, such as LORA(long range radio), NB-IOT(narrow band internet of thing) are for narrowband which can not be used to form a hybrid network with HPLC. So wireless broadband communication in electric system need to be studied. In this paper, we evaluate the performance of networking under wireless broadband communication with the reference of HPLC standard because there is not an approved standard about wireless broadband communication for electric system currently.
Design and Achievement of Security Mechanism of API Gateway Platform Based on Microservice Architecture
Authors: Dawei Yang , Yang Gao , Wei He , Kai Li 
Published: January 2021

Abstract
To solve the current security problems of the microservice architecture, the security mechanism of the API gateway platform using the microservice platform is designed and implemented. To solve the corresponding security problems, a new API platform security mechanism is designed. In the data transmission, the hybrid encryption algorithm hybridized by encryption algorithm of Rivest Shamir Adleman (RSA) and encryption algorithm of Advanced Encryption Standard (AES) is used for data encryption. An API gateway between the client and the microservice is introduced as the only entrance for users to access the microservice, avoiding the complexity of the client logic caused by the direct communication between the client and the server. After the introduction of the API gateway, the API-level service operation authority can be controlled; the security of the front-end and back-end transmission data is improved without affecting the transmission performance. The algorithm designed takes longer time than the AES encryption algorithm, but shorter than the RSA encryption algorithm, which indicates that the time-consuming of the algorithm designed is acceptable, showing the feasibility of the algorithm. The content can provide an important theoretical basis for the security of API gateway platform of microservice architecture.
Research on Key Technologies of Intelligent Operation Control of Super-large Urban Power Grid Based on Multi-center Structure
Authors: Bin Deng , Ling Zhu , Yingqi Huang , Wei Zhong , Zhenhao Ye , Jun Zhan 
Published: January 2021

Abstract
Under the background of higher and higher requirements of intelligent, reliable, green and efficient operation of power grid, the traditional operation control technology of urban power grid can no longer fully meet the new requirements of integrated operation and intelligent dispatching. The increasing environmental pollution and the gradual shortage of natural resources promote the rapid development of intelligent technology for distribution network dispatching. Traditional urban distribution network management ideas, especially the concept and mode of distribution network dispatching, can no longer adapt to the new situation, and need to be repositioned and studied deeply. In the construction of intelligent distribution network, intelligent control system is a very important part, which has a very positive significance for the overall operation of the power grid. This paper takes the construction of intelligent distribution network dispatching system as the long-term vision, extends the development and application trend of intelligent distribution network dispatching technology, and puts forward ideas on how to construct the concept and key technology of intelligent distribution network dispatching suitable for China's super large cities based on the city multi center structure.
RETRACTED: Research on Improving Computer Teaching Quality in Colleges and Universities in the Context of Big Data
Authors: Hong Wang 
Published: January 2021

Abstract
With the continuous development of information technology, big data has entered all walks of life. As an important part of college education, computer teaching is very significant for enhancing students’ computer application ability and promoting comprehensive development. However, there are still many problems in actual computer teaching in Chinese colleges and universities, and the teaching effect is not ideal. Based on this, this article will discuss the characteristics of big data, analyze the problems in computer teaching in colleges and universities, and propose measures to improve the quality under the big data environment, hoping to have certain reference.
New color image encry, tion algorithm based on double chaos system
Authors: Cun Qiqi , Tong Xiaojun 
Published: January 2021

Abstract
Due to the specific characteristics of a chaotic system described by a set of nonlinear deterministic dynamic equations, encryption based on chaos has high security. Therefore, this paper proposes a very safe and effective new color image encryption algorithm based on double chaos system. First, a true color image is divided into three channels, and under the operation of the control signal, different pseudo-random sequences generated by the Chirikov standard image are selected for XOR operation with the image pixels of a certain channel. Secondly, this paper provides a process of generating replacement boxes using one-dimensionaltial attacks and entropy-based attacks. Therefore, the algorithm has a good encryption effect and has broad application prospects in the field of image encryption.
GUI of Prediction of Gas Emission with Artificial Neural Network
Authors: Chen Daning , Zhang Mengxin , Ling Rong , Zhou Jixian , Gao Wei 
Published: January 2021

Abstract
This paper predicted the GUI of gas emission in mining face with the back propagation neural network (BPNN), the radial basis function neural network (RBFNN) and the general regression neural network (GRNN). By comparing the measured values and the prediction values, the results indicated that the BPNN, GRNN and RBFNN were capable of predicting the gas emission, and the prediction value by using the RBFNN is better than the other methods.
RETRACTED: Prediction of Water Quality based on artificial neural network
Authors: Wu Yingjia , Ling Rong , Zhou Jixian , Zhang Mengxin , Gao Wei 
Published: January 2021

Abstract
In this paper, three types of artificial neural network (back-propagation neural network, radial basis function neural network, and generalized regression neural network) were used to predict the pH values in the evaluation of water quality. Based on the measured data from the Xielugang in Jiaxin with the post-hoc analysis for the c and p values of the prediction, the results showed that the prediction within a year by using the generalized regression neural network has the lowest averaged relative error.
Design and Application of Intelligent Course Selection Algorithm for School
Authors: Qiu Guixiang , Liu Zhixu , Sun Yuye 
Published: January 2021

Abstract
Course supermarkets are emerging in many schools in China. Therefore, choosing the right courses has become a practical problem for many students. One of the primary concerns of students is to earn enough credits in a particular time limit. In this paper, we study the problem of credits maximization and evaluate the accuracy and efficiency of three different algorithms: greedy method, search method, and dynamic programming. Finally, we propose a practical implementation of the course selection algorithm that would provide new ideas for students to choose courses and suggestions for schools to set up online curriculums and course selection models.
Research on energy-saving algorithm of wireless sensor network based on penalty error matrix
Authors: Zhang Ping , Liu Meiqing , Kai SU , Han Shuhuan , Chen Wei 
Published: January 2021

Abstract
Taking into account this problems of large data volume, high frequency, and fast energy consumption in data transmission and reception of wireless sensor networks, an energy-saving algorithm based on a penalty error matrix is adopted to reduce network energy consumption. By introducing a penalty error matrix in the adaptive cubic exponential smoothing algorithm, using the principle of the minimum sum of squares of error to track the time series in real time, adjusting and obtaining the optimal smoothing coefficient in time, and it has strong adaptability to data with a large fluctuation range. The MATLAB simulation experiment results show that when the time slot range is 1500, compared with the traditional cubic exponential smoothing algorithm and the adaptive cubic exponential smoothing algorithm, the energy saving effect and prediction accuracy of this algorithm are significantly improved.
A DOA estimation algorithm based on greedy recovery under the condition of array element failure
Authors: Su Peilin , Chen Fuhu 
Published: January 2021

Abstract
Aiming at the DOA estimation when some elements in the hydrophone array fail, the conventional beamforming algorithm is not effective in estimating the direction of arrival. This paper proposes a beamforming algorithm based on greedy recovery. The ideal conditions and After the estimation effect under the failure condition of the array element, the detection performance of the method is compared and analyzed by simulation. The results show that when the failure ratio of the array element reaches 70% or more, the method always keeps the effective identification of the direction of arrival, and has better detection performance and tolerance than traditional algorithms.
The Influence of ISI and an Improved Algorithm of Channel Estimation in the Chirp System
Authors: Zhao Nan , Zhao Dongyan , Wang Yubo , Tang Xiaoke , Zhao Xu , Zhang Yubing , Liu Jiadi 
Published: January 2021

Abstract
Chirp signal is widely used in communication, radar, sonar and ultrasonic systems. The impulse response of channel must be estimated in PSK chirp spread spectrum modulation systems which is a chirp signal multiplied by the PSK modulated signal. Due to the influence of filters and multipath channel, the received signal of current symbol will be affected by the interference of the previous symbol and the next symbol, the interference which is called inter-symbol interference (ISI) can degrade the performance of channel estimation and demodulation. In this paper, based on BPSK chirp spread spectrum modulation system, we describe the received model, the channel estimation based on FFT and channel estimation of matched filtering, analyze the impacts of ISI on channel estimation. And we simulate the MSE of channel estimation and the simulation results are consistent with the analysis, then an improved method of channel estimation is proposed based on the analysis of the impact of ISI on channel estimation.
Network Situation Assessment of Host Node Based on Improved D-S Evidence Theory
Authors: He Liangyuan , Wan Tao , Zhang Chuanlin , Xia Fei , Wang Sheng , Wang Yajie 
Published: January 2021

Abstract
In recent years, network security has become a hot spot of social concern. In order to avoid dependence on network training, improved D-S evidence theory is applied to the situation assessment of host. The fuzzy function is adopted to generate the BPA of the corresponding feature, and the weighting matrix is added to handle conflict evidences in the fusion process. Finally, the situation level of the host node is obtained. The effectiveness and feasibility of the method is proved by analyses of examples.
Mobile Node Design of Indoor Positioning System Based on Bluetooth and LoRa Network
Authors: Wang Wenlong , Zang Chunhua , Chen Zilong , Liu Shuai 
Published: January 2021

Abstract
This paper introduces an indoor positioning system based on LoRa and Bluetooth network. The system uses LoRa communication protocol for network communication, and uses Bluetooth technology to locate the mobile node in the indoor area. The positioning data is transmitted through LoRa network to realize real-time accurate positioning in a large area. The system is composed of mobile nodes, Bluetooth beacons, LoRa gateway, etc., which has low power consumption and low cost, flexible deployment, high performance and other features, can be widely used in large industrial parks that need to locate personnel and equipment and all other indoor positioning scenarios.