bluuebunny/crossref_metadata_2025 huggingface dataset:
Theoretical study on martensitic-type transformation path from rutile phase to α-PbO2 phase of Ti2O*
Authors: Wang Wen-Xuan , Jiang Zhen-Yi , Lin Yan-Ming , Zheng Ji-Ming , Zhang Zhi-Yong
Published: April 2020

The martensitic-type phase transformation paths from the rutile to the α-PbO2 phase of TiO2 are studied with linear interpolation and NEB/G-SSNEB methods based on first-principles calculations. Its potential energy surface and the lowest energy path are revealed. Our results indicate that the titanium atoms of the rutile phase shuffle along the [0–11]rut crystal direction to form the α-PbO2 phase. During the phase transition, the oxygen atoms are dragged by the heavier titanium atoms and then reach their new equilibrium positions. The barrier of phase transition from nudged elastic band theory is about 231 meV, which is qualitatively consistent with previous theoretical calculations from the monoclinic phase to the tetragonal phase for ZrO2 and HfO2. Debye model can also be successfully used to predict the pressure and temperature of the phase transformation.
Prediction Model of Red Tides in Fujian Sea Area Based on BP Neural Network
Authors: Wang Jingyan
Published: April 2020

This paper presented a new model of the red tide in Fujian Province by BP neural network (BPNN) based on five sets of marine condition data between 2015 to 2019. Data cleansing and normalization were applied before the training. The 12-fold cross-validation reduced the shortage of data. As a result, this model could get a related correct prediction of red tide in this particular area.
The Communication Network Scheme Based on EPON and Industrial Ethernet Technology for Smart Distribution Network
Authors: Zhang Hongmei , Huo Xiaoliang , Cheng Nan , Zhang Ji , Xie Yantao
Published: April 2020

In order to meet the demand of security zone and reliable transmission for the business in smart distribution network, this paper proposes a communication network scheme based on EPON and industrial Ethernet technology on the basis of analysis for business requirements. The scheme using the advantage of EPON and industrial Ethernet technology, transmits different partitions business on distribution network. The analysis shows that the scheme can improve the reliability of transmission while guaranteeing the business security. It has reference value for the planning construction of smart distribution network.
PS-HOMO: A Protection Scheme for iOS SMS
Authors: Zhou Guomiao , Wu Qianqiong , Duan Ming , Xi Qi
Published: April 2020

iOS Short Message Service (SMS) transmits messages in plaintext, which would lead to potential security threats of data. It is meaningful to design a safe and effective SMS. In this paper, all iOS Security Guides are referred to and all the cryptographic algorithms in iOS data protection are analyzed. Because there is no homomorphic encryption, a library of homomorphic encryption algorithms for iOS based on RSA and Paillier is developed. Using this library, a protection scheme PS-HOMO for protecting iOS SMS data is proposed and implemented. Under the premise of ensuring the data confidentiality, PS-HOMO also has the function of ciphertext operation due to the multiplicative homomorphism of RSA and additive homomorphism of Paillier. A comprehensive performance test was performed on PS-HOMO. The results show that the performance is in line with our expectations and will not have a major impact on the original system. The security of PS-HOMO is theoretically analyzed from man-in-the-middle attack, replay attack, and traffic analysis attack. Two application scenarios of the PS-HOMO, remote anonymous voting and privacy telemedicine service are envisaged. We hope PS-HOMO would play a significant role in privacy protection.
Research on multimedia technology of physical education classroom combined with computer platform
Authors: Zhao Xiuqiang
Published: April 2020

With the rapid development of the economy, the development of information technology is also relatively rapid, and informational teaching is being valued by more and more educators. The organic combination of information technology and classroom teaching can not only stimulate students’ interest in learning, but also improve students’ learning efficiency, thus enhancing the quality of teaching. Therefore, teachers should enhance the concept of high technology when teaching, and combine information technology with teaching methods. This paper mainly analyzes the application status and existing problems of information technology in physical education classroom, and discusses the application strategies of information technology in physical education, so that people can raise awareness of information technology.
Research on the influence of hidden layers on the prediction accuracy of GA-BP neural network
Authors: Xing Yuhua , Li Fanfei
Published: April 2020

In order to improve the prediction accuracy of GA-BP neural network, the effect of hidden layer neurons number on the prediction accuracy of algorithm was considered and an improved GA-BP neural network was proposed. Taking 60 equipment maintenance time of a photovoltaic charging station as the specimens, the high prediction accuracy of improved GA-BP neural network has been proved. Results indicate that the GA-BP neural network has the highest prediction accuracy when the number of hidden layer neurons is 5. The average relative error of improved GA-BP neural network between the predicted values and the expected values is 6.1%, decreasing 57% compared with BP neural network. The prediction accuracy of improved GA-BP neural network is much higher than that of BP neural network, and the predicted time can provide a basis for personnel scheduling.
Test Platform for Intelligent Internet of Vehicles Video Exchange System
Authors: Jiao Qingchun , Zhan Deyou
Published: April 2020

Intelligent Internet of Vehicles is the hot spot of current traffic industry, Video information as a very important part of multidimensional perception, is widely used in vehicle-vehicle interconnection, vehicle-road interconnection and vehicle-management platform interconnection. Because there are obvious differences in the efficiency level between different methods and devices in specific operation, relevant video exchange testing and verification become necessary. This paper presents a test platform and method for video information exchange in Intelligent Internet of Vehicles.Through this platform, a combination of subjective evaluation of video streams and objective testing of transmission network is used to test the availability of the test platform for video exchange on the Internet of Vehicles.
Passenger Flow Prediction based on Recurrent Neural Networks and Wavelet Transform
Authors: Huang Jing , Shao Fubo , Yang Shuguo
Published: April 2020

It is a great significance for the accurate and real-time prediction of passenger flow in rail transit operation. In the process of passenger flow prediction, the new method of recurrent neural networks (RNNs) can well solve the problems of randomness and nonlinearity which can not be solved by the existed linear models. In this paper, the long short-term memory (LSTM) and the gated recurrent unit (GRU) networks, which are methods of RNNs, are employed to predict the dayparting passenger flow and the raw passenger flow data is denoised by the wavelet transform. Experimental results show that LSTM and GRU networks can well predict the passenger flow. And compared to LSTM, GRU is better for passenger flow prediction.
Design and Implementation of Roadside Intelligent Information Interaction System Based on Edge Computing
Authors: Guang Yang , Dongbo Liu , Chaofeng Ma
Published: April 2020

Under the influence of artificial intelligence (AI), Internet of Things (IOT) and big data technology, V2X vehicle infrastructure cooperative technology is rapidly applied to intelligent traffic management and road condition services. However, the existing roadside traffic control equipment has difficulty in data aggregation and processing, that cannot meet the application requirements of the intelligent connection and edge calculation of the V2X vehicle infrastructure cooperative device. In this paper, the “edge computing + end-edge-cloud collaboration” mode is used to construct the roadside intelligent information interaction system. As an intelligent connection node between roadside traffic management system and V2X vehicle infrastructure cooperative system, the design makes roadside video analysis and real-time data fusion and push function come true. Because of its lightweight intersection deployment mode, regional-level road condition diagnosis and optimization control capabilities, it has broad application prospects.
The Trajectory Generation of UCAV Evading Missiles Based on Neural Networks
Authors: Zhang Hongpeng , Huang Changqiang , Zhang Zhuoran , Wang Xiaofei , Han Bo , Wei Zhenglei , Li Yingtong , Wang Le , Zhu Wenqiang
Published: April 2020

In order to solve the problem of evading air-to-air missiles of UCAV in autonomous air combat, the flight dynamics model and 3-dimensional guidance trajectory model based on proportional guidance were established and performance constraint conditions of missiles were constructed. According to the definition of basic maneuver library, 72 kinds of avoidance maneuvers were constructed. All 72 avoidance maneuvers were simulated while UCAV was at different relative yaw angles and relative pitch angles, and the optimal avoidance maneuvers under the corresponding conditions were selected out. Training samples and test samples were constructed by utilizing the acquired data, and the neural network for generating control parameters was trained. Under different conditions, neural network method and random selection method were simulated. The results show that the success rate of escape of the proposed method is higher and the time cost of generating the control parameters is less, which meets the requirements of effectiveness and real-time.
Research on Seasonal Prediction of PM2.5 Based on PCA - BP Neural Network
Authors: Zhang Yi-wen , Yuan Hong-wu , Wu Hai-long , Sun Xin , Dong Yun-chun
Published: April 2020

PM2.5 is a kind of data with strong time-series characteristics, so the current PM2.5 prediction methods mostly choose RNN, LSTM and other sequence models for prediction, but because RNN, LSTM and other models use the same weight to calculate the data input at different times, which does not conform to the brain-like design, resulting in a low accuracy of PM2.5 concentration prediction. In view of the above problems, a PM2.5 prediction method based on attention mechanism (at-rnn and at-lstm) is proposed. This method firstly establishes the encoder-decoder model based on deep learning. In the Encoder stage, attention mechanism is added, and attention weight is allocated to the input with time series characteristics, and then Decoder analysis and prediction are carried out. Through experiments, the effects of RNN, LSTM, at-rnn and at-lstm on the prediction of PM2.5 concentration in hefei are compared. The results show that the accuracy of the prediction method based on attention model is better than other methods, indicating the effectiveness of the prediction method based on attention model in the prediction of pollutants.
A Method for Improving Bandwidth of Multimode Optical Fiber Network
Authors: He Kun , Guo RiCheng , Cui Can Wang , Feng Guo Kai , Ying Wang
Published: April 2020

A high-speed data exchange network based on multimode fiber and RapidIO technology is widely used in existing projects. It consists of a fiber switch and a high-speed interface module. The fiber switch is used as the data exchange core to complete protocol conversion. The high-speed interface module is connected to the universal device node and is responsible for access conversion of the RapidIO bus between the optical network. The hardware design utilizes the commercial shelf architecture, the software design adopts a multi-buffer and multi-thread data exchange method to increase the entire network bandwidth from 300MB/s to 800MB/S.
Pig target detection method based on SSD convolution network
Authors: Deng Minghui , Yu Ran
Published: April 2020

The behavioral changes of pigs can not only reflect their own health and welfare status, but also have important significance in improving the breeding environment. Rapid and accurate detection of pigs’ targets is the basis of behavioral change analysis.In view of this situation, a target detection algorithm based on deep learning is proposed, and its model structure and working principle are expounded. Then, through the test of pig image data set, the results show that this method can accurately detect pig targets under complex background.
Bi-objective Optimization of Black Start Allocation for Regional Power Grid
Authors: Cheng Xue , Zhao Yanjun , Long Fei , Wang Qian , Wang Hongtao
Published: April 2020

Under the influence of extreme weather events, black start allocation is more and more important for regional power grids lack of hydroelectric units and pumped-storage aggregates. This paper proposes a bi-objective optimization model considering both the time of the whole restoration and the risk of line recovery, an improved TOPSIS method is employed to solve the problem based the non-inferior solution. The results of the Dongguan power grid verify the effectiveness of this method.
An Improved B-A Model for Scale-free Network Evolution Model
Authors: Wei Hongyan , Wang Jiangong , Wang Tianqi
Published: April 2020

Scale free network can describe complex network very well. Barabasi and Albert proposed B-A model, which reveals the nature of many complex phenomena in the real world. The generated network degree distribution satisfies power-law distribution. In this paper, two shortcomings of the model are found through careful study, and an improved scale-free network evolution model is proposed. The experimental data show that the improved model has significant scale-free characteristics and can better reflect some characteristics of complex networks.
Crowd Counting via Multi-Column Deconvolution Networks
Authors: Jiang Jibing , Bai Mengxuan , Liu Bo , Zhou Guihong
Published: April 2020

The difference in distance between the crowd and the camera results in different scales of the population in the image. In the study of crowd counting, this paper first proposed the method of adding deconvolution to multi-column network for the problem that the population size in the image does not affect the accuracy of counting, namely multi-column deconvolution neural network (Mutil-Column Deconvolutinal Neural Network, MCDNN). Compared with the results of the Multi-Column Convolutional Neural Network (MCNN) on the ShanghaiTech dataset, the MSE is reduced by 42.8 and the MAE is reduced by 26.6. On the UCF_CC_50 dataset, the MSE is reduced by 109.4 and the MAE is reduced. 86.3. Compared with other advanced methods, the proposed MCDNN network achieves better performance on the data set, effectively solves the problem of inaccurate population counting accuracy due to scale changes, and can generate a better quality density map.
The Research and ImplementationOf The Application Technology Of Domestic Basic Software In The Security Information System
Authors: Chen Hongyan , Wang Sihong , Wan Junwei , Li Zhen
Published: April 2020

This article aims at the typical application scenarios of high-density integrated application information systems. It investigates, sorts out, and analyzes the specific application requirements of domestic software such as middleware, databases, operating systems, and office software. According to the characteristics of the high-density integrated application information system, a set of system architecture based on domestic basic software is constructed, the feasibility of the domestic basic software applied to the high-density integrated application information system is analyzed, and its application in the high-density integrated application information system Models and solutions for different application scenarios (reporting, information services, information sharing, collaborative office, etc.).
Application of Information Technology in Construction Machinery Management
Authors: He Yizhou
Published: April 2020

Construction machinery is a key factor in the construction of construction projects, which is of great significance for ensuring the quality and schedule of construction projects. Many problems have arisen in the current management of construction equipment, which have a negative impact on the reliability and sustainability of construction equipment. Emphasizing the quality of construction equipment management work and optimizing the application of information technology in construction machinery management can effectively improve the continuity of machinery equipment operation. This article will systematically discuss the application research ideas of information technology in the management of construction machinery, and put forward related suggestions based on the actual situation.
Wafer SEM Image Generation with Conditional Generative Adversarial Network
Authors: Du Huqiang , Shi Zheng
Published: April 2020

Scanning Electron Microscope (SEM) images play an essential role in the analysis and evaluation of the defects of the circuit in advanced integrated circuit manufacturing. Currently, the image generation method is a useful means to solve the insufficiency of wafer SEM images due to the high cost of getting a large number of labeled SEM images. In this paper, an algorithm based on conditional generative adversarial network (cGANs) is proposed for SEM image generation. Firstly, a Sobel operator is used to calculate the gradient information of images to guide the discriminator. Then we apply two discriminators to discriminate images of different resolutions. Finally, Wasserstein distance and smooth L1 loss functions are applied to accelerate network convergence. Experimental results show that this method could learn to mimic the distribution of wafer SEM image data effectively. Compared with other image generating models, our model improves the quality of the generated image, and its 1-Nearest-Neighbour (1-NN) classification score is increased by 0.3. Therefore, this algorithm is more suitable for generating images to alleviate the shortage of wafer SEM images.
Analysing the efficiency and robustness of gossip in different propagation processes with simulations
Authors: Yang Ruiqi
Published: April 2020

This paper uses the probability theory to analyse the ultimate consistency of the gossip protocol propagation process by dividing it into two phases. The time complexity and information complexity of the flooding, tree and gossip methods are compared by simulation with different variants. Also, three ways of communication between nodes in the network are introduced: only-push, only-pull, and push-and-pull. The paper analysed the simulated results of variable nodes using those three ways and discussed their corresponding time and information complexity. The simulations and analysis compared performances of information transmission under different transmission loss rates and concluded that the push-and-pull has an effect on transmission structure robustness. Finally, an effective method of information transmission was proposed to deal with transmission loss.
An analysis on the current researches in encryption algorithms based on neural networks
Authors: Ouyang Jin
Published: April 2020

To perform an in-depth analysis on the current researches concerning the application of neural networks in the encryption algorithms, this paper used some research methods such as literature review and algorithm analysis to review the proposal and application of neural network technologies as well as the proposal and research and development of encryption algorithms through. The importance of neural networks in the encryption algorithms is highlighted. The current researches on encryption algorithms based on neural networks are reviewed from three dimensions, namely, algorithm framework, algorithm model and algorithm application. Through the research, it shows that the neural network technology has become the preferred choice for developing the encryption algorithms. This paper also proposed the direction of improvement through fusion application of multiple information processing technologies. This work lays the basis for improving the encryption algorithms based on neural network.
Analysis of and Reflections over the Development of New Energy Automobile and Intelligent Manufacturing
Authors: Yayu Qiu
Published: April 2020

With the rapid socio-economic development and technological upgrading, various advanced technological achievements have emerged. Nowadays, people are paying more attention to a low-carbon environment, especially the new energy, when faced with energy shortages and serious environmental pollution. It is known to us all that cars can cause serious environmental pollution. That’s why great attention has been paid to the development and application of new energy vehicles, which can not only save energy and protect the environment, but also meet people’s basic needs. The Chinese government has given strong support to new energy vehicles in terms of funding, technologies, policies, and incentive measures. At present, new energy vehicles are in the stage of development and manufacturing. Its industrial chain has been formed and is now moving towards intelligent manufacturing, with various supporting units progressing rapidly. This paper focuses on the issues related to the development of new energy vehicles and intelligent manufacturing.
An Enhanced Nonlinear Hybrid Precoding Algorithm for Millimeter Wave Massive MIMO Systems
Authors: Liu Fulai , Zhang Yanshuo , Du Ruiyan
Published: April 2020

Hybrid precoding has recently received considerable attentions in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Especially, a nonlinear hybrid Tomlinson-Harashima precoding (THP) algorithm has recently received considerable attentions since it can effectively improve the performance of the hybrid precoding. This paper presents an enhanced nonlinear hybrid Tomlinson-Harashima precoding algorithm based on the column-by-column refinement (named as E-THP-CR algorithm). Compared with the previous works, the proposed algorithm offers a numberof advantages.The advantageof the proposed algorithm lies in achieving the column-by-column refinement of the analog precoding matrix. Afterwards, the digital precoding matrix is decomposed into two separate sections which respectively belong to the encoding part and effective channel part. This design can effectively remove the inter-user interference as expected in the THP module. Simulation results verify that the proposed algorithm provides higher spectral efficiency, compared with the other relevant algorithms.
Ordering of matching energy and Hosoya index of tricyclic graph
Authors: Suo Langwangqing , Tian Shuangliang , Yang Qing
Published: April 2020

The matching energy of a graph G is defined as the sum of the absolute values of thezeros of the matching polynomial of G. The Hosoya index of a graph G is defined as the total number of matchingsof G. In this paper, the matching energy and Hosoya index of the a special class of tricyclic graphs G(m
1, m
2, m
3) were investigated, and orderings of tricyclic graphs G(m
1, m
2, m
3) with respect to matching energy and Hosoya index are obtained.
Design of Traffic Coordination Control Structure Based on Multi-Agent
Authors: Yong Huang , Li Gan
Published: April 2020

Urban transport, one of the city’s important infrastructures, which plays an important role in the normal functioning of the city, has become the focus of attention and discussion in the whole society. Restricting to the sustainable development of urban economy, the traditional solution to the urban traffic problems can no longer meet the development requirements of existing urban traffic. Given the complexity of urban transport, the limitations of traditional traffic control methods and the popularization and application of mature artificial intelligence technology, this paper discusses the collaborative framework of traffic control and induction on the base of multi-Agent technology and make researches on the structural design of urban traffic coordination control, thus builds a simulation model for the single intersection. The simulation experiment was carried out by using the Q learning algorithm.
Intelligent Deformation Control Algorithms for Mechanical Metal Parts Based on Internet of Things
Authors: Li Bohua
Published: April 2020

In order to solve the problem of serious damage during the operation of mechanical metal parts, the intelligent control algorithm of deformation of mechanical metal parts is studied based on the Internet of Things technology. Firstly, the characteristic parameters of deformation of metal parts are collected by the fuzzy algorithm, and the extreme value of damage degree of parts is evaluated and calculated by the artificial ant colony algorithm. According to the calculation results, the deviation parameters of the moving trajectory of the mechanical metal parts are corrected to alleviate the damage of the metal parts, so as to realize the intelligent control algorithm for the deformation of the mechanical metal parts. Finally, the experiment proves that the intelligent deformation control algorithm based on the Internet of Things has better practical value than the traditional algorithm.
A mobile robot path planning algorithm based on improved A*
Authors: Shi Jinzheng , Su Yifan , Bu Chunguang , Fan Xiaoliang
Published: April 2020

Global path planning of mobile robot aims to provide a safe and smooth path for mobile robot navigation. Traditional A * algorithm is planning the path of more turns, and not smooth. Moreover, for the u-shaped terrain, the path stick to the obstacles. Aiming at the shortcomings of A* algorithm, cosine distance is selected as the heuristic function, and direction information is added and normalized. The 36-order neighborhood search matrix is selected to solve the problem of fitting u-bend. In addition, a post-processing method based on Bessel curve is proposed. Make the planned path curvature change continuously. Simulation results show the effectiveness of the improved algorithm.
Real-time Online Fault Diagnosis of Rolling Bearings Based on KNN Algorithm
Authors: Wang Haiya , Yu Zhongqing , Guo Lu
Published: April 2020

In order to realize the predictive maintenance of rolling bearings in industry, this paper proposes a real-time online fault diagnosis method for rolling bearings based on KNN algorithm. The method mainly includes two steps: fault diagnosis model training and real-time online fault diagnosis. Firstly, the vibration signal is preprocessed: data classification, data cleaning, data segmentation and feature parameter extraction, and then training and optimizing the fault diagnosis model. In the real-time online fault diagnosis part of the rolling bearing, the real-time online extraction of the characteristic parameters of the vibration signal is used to realize real-time online fault diagnosis through the fault diagnosis model. The results show that the fault diagnosis model based on KNN algorithm is better than the fault diagnosis model based on C4.5 algorithm and CART algorithm, which is more suitable for fault diagnosis of rolling bearings. Using this method to diagnose rolling bearings can help predictive maintenance before rolling bearing failures and reduce the economic losses caused by unplanned downtime of critical equipment.
RETRACTED: Building Logistics Block Chain Platform Based on Cloud Computing
Authors: Chen Huihong , Liu Shiming
Published: April 2020

With the rapid development of the new generation of information technology and e-commerce, the modern logistics industry chain has emerged. The logistics blockchain platform enables all kinds of users to participate in the whole information transmission process together. It establishes the logistics blockchain cloud platform deployment jointly participated by the government, enterprises, schools, institutions and communities. According to the practice, different blockchain deployment modes are adopted, A new multi agency data sharing framework is designed to promote the application of blockchain in the logistics industry.
Target part detection based on improved SSD algorithm
Authors: Yu Yongwei , Han Xin , Du Liuqing
Published: April 2020

Aiming at the problem that the traditional target detection algorithm cannot balance the target detection accuracy and real-time detection, and the detection effect is poor under the actual complex production conditions. A deep learning detection method based on Inception-SSD framework is proposed. The Inception-SSD, which integrates the Inception prediction structure, introduces the Inception block into the extra layer of the SSD network. Then it uses batch normalization (BN) and residual structure connection to capture more target information without increasing the complexity of the network. It will improve its accuracy without affecting its real-time detection. The result of the experiment show that the detection accuracy of this model is 97.8% in the actual production process, which is largely improved comparing with the original SSD algorithm. The detection time is 48ms, which improves the detection accuracy and ensures the real-time performance. It can meet the detection requirements of parts in actual production.
An algorithm based on the dichotomy for quickly identifying whether a sequence is a PAPR sequence
Authors: Yang Yaoqi , Zhang Lei , Guo Xiao , Xu Renhui
Published: April 2020

With the development of communication technology, OFDM (Orthogonal Frequency Division Multiplexing) technology has become one of the core technologies in the field of wireless communication. Although OFDM has many advantages, it has a problem that the ratio of peak-to-average ratio is too large, that is, the PAPR problem. Despite the achievements in the technical means of suppressing PAPR (Peak to Average Power Ratio), the implementation of new technologies often requires the introduction of excessive IFFT calculations. Based on this situation, this paper proposes a new algorithm based on binary search to solve this problem.
The Research on autopilot system based on lightweight YOLO-V3 target detection algorithm
Authors: Gao Xiulong , Ge Dongyuan , Chen Zhifeng
Published: April 2020

Computer vision is one of the most important branches in the field of deep learning, which includes image classification, target detection and so on. In this paper, the pruning algorithm is combined with the method of reducing the network depth, and the trained network model is applied to the field of autopilot, which solves the problems of high power consumption, single function and poor real-time performance of the vehicle target detection system. In this paper, through a large number of theoretical research and experiments, the appropriate activation function and regularization method are selected. Through the visualization method of neural network convolution layer, the working principle of the network is expounded in detail. Through theoretical analysis, the appropriate anchor box, is selected and the non-maximum suppression algorithm is introduced. Tensorboard data visualization system is used to monitor the distribution and law of network parameters. The accuracy of detection according to the experimental target is 98.7%.
A General Algorithm for Rectangular Parking Optimization Design
Authors: Huang Junhao , Liao Tianchi , Kang Haining , Wang Jianjun
Published: April 2020

The optimization design of parking is a comprehensive programming solution with a relatively large practical value. Determining the optimal design of the parking lot is the main goal of this paper. Before the algorithm design, this paper first deduces the calculation formula of the width of the lane in the parking lot; then refines the parking lot design problem into the choice of the layout of the double-side parking channel and the layout of the single-side parking channel, and the choice scheme is based on the greedy algorithm. On this basis, we establish a general optimization design algorithm for the rectangular parking lot, which is essentially a programming algorithm. Finally, this paper selects an example to solve the general algorithm by SA algorithm. It proves that the general algorithm meets the requirements and has practical value.
Response Calculation in Zero Memory Nonlinear System Based on Digital Filter Method
Authors: Xu Fei
Published: April 2020

Analysis of dynamic characteristics of structures often relies on linear theory in many practical applications. However, almost all structures show nonlinear characteristics when experienced with large enough excitations. Firstly, calculation of forced response in linear dynamic system using digital filter method is presented. Then, linear system is extended to nonlinear system. The nonlinear restoring force is treated as external loads and used to derive a generalized mathematical model to calculate the forced response in zero memory nonlinear system based on digital filter method. Finally, the ‘Reverse Path’ and multiple coherence function are used to estimate the frequency response function of underlying linear system. Numerical simulation of a multiple degree of freedom system with multiple nonlinear elements is used to verify the presented method. The results indicate that the presented model works well for calculating the forced response in zero memory nonlinear system.
Range and Standard of Yang Dongfang Spatial Water Temperature Variation Angle II. Spatial Water Temperature Model Application
Authors: Yang Dongfang , Tao Wenliang , Wu Yunjie , Wang Ming , Huang Chengling
Published: April 2020

According to the investigation materials in the water field of Jiaozhou Bay in May, August and October 1979, this paper studied the rise, decline and changing process of water temperature in the surface and bottom waters. Based on the definition and model of Yang Dongfang spatial water temperature variation angle, the results indicated that in the waters from inside of the bay mouth to the around from May to October, the range interval of the Yang Dongfang water temperature variation angle is 1.14°in the surface and 6.27°in the bottom when heated is the surface of a water body; from the waters in the bay mouth to the waters outside, the range interval of the Yang Dongfang water temperature variation angle is 13.49°in the surface and 4.00°in the bottom when cooled is the surface of a water body, which displays the changing process of the water temperature when heated or cooled is a water body.
Application Of A Template Matching Algorithm In The Detection Of The Railroad Track
Authors: Wang Cenan , Fu Xiangyi , Shi Chaoxiong , Zeng Qiwen
Published: April 2020

As the most important part of urban public transportation system, railway and subway are undertaking extremely important tasks. Manual inspection is sometimes difficult to detect track damage in time. Based on the impulse excitation of the rail, the undamaged rail and the damaged rail are distinguished according to the characteristics of its vibration signal. In the process of feature extraction, the pulse signal is intercepted, and the threshold is taken after gaussian smoothing filter. After multiple processing, the feature template is formed. Through the template matching algorithm proposed in this paper, the rail excitation pulse signal can be identified and the rail damage state can be determined. And the simulation display and control platform based on real object is made. After many tests, the method is proved to be effective.
Research and design of intelligent parking system based on 5G technology
Authors: Luo Wanbo
Published: April 2020

In order to solve the parking problem, such as difficult parking, low efficiency parking space sharing, incomplete parking management and high cost of traditionalparking, an intelligent parking system in city based on the 5th Generation Mobile Communication Networks (5G) is proposed in this paper. 5G mobile communication technology has two important advantages of high transmission rate and low transmission latency, so it can better satisfy the rapid development of the Internet of Things (IoT). The intelligent parking system architecture in city based on 5G has six layers, including Parking IoT layer, intelligent gateway layer, 5G mobile communication network layer, access point name (APN) enterprise private line access layer, cloud computing and big data layer, intelligent parking system management layer.
An improved ABC algorithm approach for shape optimization of the blood centrifugal pump impeller
Authors: Wang Jiaming , Ruan Xiaodong , Fu Xin
Published: April 2020

A high efficiency blood centrifugal pump has low blood damage and little energy loss, so it is important to improve hydraulic efficiency by optimizing the design. In this paper, an improved Artificial Bee Colony algorithm combined with the adjoint method (ABCA) is proposed to optimize the blood centrifugal pump impeller. The introduction of gradient information enhances the search performance and the convergence judgment of ABC algorithm. Besides, its random search feature can effectively avoid the adjoint optimization method from trapping in local optimum. The ABCA algorithm are applied to increase the hydraulic efficiency of a self-designed blood pump. After optimization, five design parameters of the impeller are optimized, and hydraulic efficiency of the impeller improves about 3.90%. Compared with ABC algorithm, the ABCA algorithm saves about 58% of calculation time, and its convergence performance is much better than ABC in the middle of the iteration.
Research on the Impact of Artificial Intelligence Technology on Accounting
Authors: Li Chaoyi , Haohao Song , Ming Fu
Published: April 2020

The rapid development of artificial intelligence has promoted many changes in the field of modern accounting. This paper examines the impact of artificial intelligence on accounting business, accounting theory and accounting personnel’s ability in recent years through literature research. The conclusions show that: First artificial intelligence makes the accounting staff liberation from a low level repetitive work out, the original focus of financial accounting change for the company to provide information to support business decisions; Second, management accounting theory, value creation theory and management intelligence mechanism The intersection of theory and artificial intelligence promotes the development of accounting theory. Third, financial expertise of accountants demanding, complex multi-disciplinary background and with universities and businesses.
LoRaWAN Anti-collision Algorithm Based on Dynamic Frame-slotted ALOHA
Authors: Xiongfei Liu , Yunyi Zhu , Liao Beiping
Published: April 2020

With the exponential growth of IoT devices, new challenges have been placed on the scalability and reliability of LoRa networks. At present, the collision problem of the LoRa network is serious. This is because its MAC layer protocol LoRaWAN is mainly based on the pure ALOHA mechanism, which is too simple to handle the collision. The dynamic frame-slotted ALOHA algorithm is optimized on the pure ALOHA algorithm, which can effectively reduce the collision. Therefore, this paper combines the dynamic frame-slotted ALOHA algorithm with LoRaWAN to dynamically divide one cycle into multiple frames. Through the LoRa preamble detection technology, the intra-frame slots are divided into idle time slots, single time slots and collision time slots. According to the number of slots, the optimal frame length of the next frame is estimated. Besides, the paper studies the initial frame length ratio. The simulation experiment is carried out on the LoRaWAN model on ns-3, which verifies that the algorithm can effectively improve the Packet Delivery Ration and System Efficiency.
Improved Parallel Genetic Algorithm Based on Resetting Strategy and Hash Table
Authors: Lu Peng , Xiao Xiaoqiang , Wang Jijin , Ning Weixun
Published: April 2020

In the process of parallel genetic algorithm (PGA) convergence, the probability of generating repeated individuals in a new generation is gradually increasing, which leads to repetitive computations of fitness values. In order to improve the time-efficiency and quality of solutions, an improved algorithm based on resetting strategy and hash table (RHPGA) is proposed. On the one hand, RHPGA takes advantage of the low time complexity of hash table lookup to reduce fitness values’ calculation of repeated individuals. On the other hand, RHPGA uses a resetting strategy to improve the optimal solution searching ability. By solving a set covering problem, PGA and RHPGA are compared. The experiment proves that RHPGA can almost increase the time-efficiency by 300% and quality of solutions by 15%.
Design and Implementation of a Simulation Training Platform for Performance Measurement of a Radar Transmitter Sub-system
Authors: Deng Bin , Wang Jingjing , Li Chuanqi , Li Yiyuan
Published: April 2020

In order to improve the parameter testing ability of radar equipment support personnel, it is urgent to provide an effective training platform for the army to carry out parameter testing training. In this paper, according to the actual test requirements of radar equipment launching subsystem, the functional requirements of the simulation training platform were analyzation, the parameters of the launching subsystem test training were determined, the overall design scheme of the system was proposed, and the software and hardware design of DDS module, local vibration module and other key functional modules were given. The practical application shows that, on the one hand, the students can be better familiar with the signal flow of the radar transmitting subsystem and understand the working mechanism. On the other hand, it can ensure that students can carry out the measurement practice of transmitter performance parameters in a safe environment and improve their testing skills. The successful development and popularization of the platform can effectively alleviate the contradiction between more people and fewer machines in equipment testing practice, and help to improve the benefits of equipment teaching.
Radio Anomaly Signal Recognition Methods Based on Clustering
Authors: Li Shengyang , Lin Jianxi , Tian Bin , Shen Li , Cui Guorong , He Jing
Published: April 2020

Identifying radio anomalies is one of the main purposes of radio monitoring. The current radio anomaly signal identification is mainly finished manually by the radiops, using professional radio knowledge and their work experience. However, because the anomaly signal is hidden in the “massive” data, accompanied by a large amount of noise, and also data imbalance, the anomaly signal is difficult to find. In this paper, we combine the data unevenness processing method SMOTE and the (guorong: cluster detail) to identification the anomaly signal during radio monitoring. Experimental results show that our method can improve the efficiency of existing radio anomaly signal recognization. Moreover, our experiments also shows that data imbalance processing plays a key role in anomalyq signal recognition.
Research on high robustness 4.5kV FRD chip
Authors: Liu Jiang , He Feng , Liu Yueyang , Jin Rui , Dong Shaohua , Gao Mingchao
Published: April 2020

A robustness 4500V/100A FRD with was designed by simulation and verified by experiment. The chip composed with optimized carrier density cell area and ruggedness terminal area. The cell area composed of P-body/N-sub/N+ layers, has good static and dynamic trade off characteristics by carefully design. The simulation show that there was no difference between conventional multi-deep P-ring terminal and multi-deep P-ring plus inner field plate terminal. Both terminals have the same width and almost the same breakdown voltage, low electric field and etc.by simulation.The experiment show that different terminal chips have almost the same trade off characters but different in reliability test, the inner field plate terminal pass 1000H HTRB test while the conventional multi-deep P-ring terminal failed at 168H HTRB test.
Railway Track Circuit Signal State Check Using Object Detection
Authors: Li Bin , Wu Suining , Wang Zhixin , Chen Xiaoguang , Shi Long , Tan Shulin
Published: April 2020

The track circuit is widely used in the railway network for safety, and the corresponding track circuit equipment is laid almost every railway station, which provides an extremely important information service for the safe driving of the train. In this paper, we proposed a two-phase detection algorithm for the state of the signal equipment of the track circuit, which is used for automatic safety detection of the status of the track circuit signal equipment in the railway signal room. Compared with the traditional inspection method of inspection workers, our proposed detection algorithm of signal state greatly improves the efficiency of security inspection, and in the experimental results, the proposed method outperforms other methods in different situations.
Study on the Textural Complexity of Black Thang-ga Image
Authors: Zhange Weijiang , Dang Hongshe
Published: April 2020

In order to study the characteristics of Thang-ga image, this paper studied the texture complexity of black Thang-ga image. The complexity model of image texture was constructed. The texture complexity of black Thang-ga image was calculated by using the textural complexity model. Furthermore, 113 images in the black Thang-ga data set were analyzed. The maximum, minimum and mean of texture complexity of Thang-ga image in data set were calculated. The data shows that the black Thang-ga image is a kind of textural complex images.
Efficient rail repair machine based on image recognition technology
Authors: Yang Menglan , Luo Laizhen , Tao Menglun
Published: April 2020

In this project, the detecting bolt loosening technology uses the CMOS camera for image acquisition, and the image is extracted by the FPGA combined with the single-chip computer. The author calculates the relative rotation angle of the bolt mark symbol before and after loosening by image analysis technology, through which we can quantify the loose angle of bolt and judge bolt’s loose condition. Then, the author uses the bolt screw maintenance machine to screw the loose bolt, which can achieve the purpose of repairing the loose bolt. This paper is of great significance in providing a theoretical basis for the theoretical design and practical engineering application of the rail maintenance machine.
Research on BIM Model Identification System for Substation Project Management
Authors: Qi Xuan , Liu Yunfei , Zhang Yang , Cao Sheng , Zhu Wenrui , Tang Juejing
Published: April 2020

In the current construction of the Internet of Things, informational data has become an important technical content. Among them, information classification and coding are the basis of informational data construction. In the BIM (Building Information Modeling, 3-dimension information model) project management, the identification system code is used as the encoding carrier by the BIM model. Through the coding, the corresponding physical model objects can be found, which makes the information database more clear and complete, and helps to apply the life cycle database. At present, the application of BIM technology to substation engineering management is a relatively new field. The corresponding BIM identification system coding research work is not enough, and the traditional KKS identification system shows great defects in the current professional technical rules and application of the project management platform using BIM technology. This paper aims to improve the BMS technology project management by substation BIM technology project based on the existing KKS identification system framework, through unifying coding format, enhancing coding level identification, creating substation building code identification and prominent electrical main professional identification. To form a three-dimensional model identification system and apply it to substation BIM technology project management and carry out practice in actual engineering projects. To realize the accurate delivery and standardization of BIM model information data by the life cycle information management platform.