bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Class Weighted Algorithm for PSVM
Authors: Zhu Xiaorong , Zhang Qian , Qiao Sai 
Published: November 2020

Abstract
Focusing on the problem of slow training speed existing in the SVM in intrusion detection, this paper improves the faster PSVM (Proximal SVM) method and proposes a new kind of class - weighted PSVM algorithm. This kind of algorithm not only has a fast classification speed, but also improves the classification accuracy.
Multi-Robot Path Planning Method Based on Prior Knowledge and Q-learning Algorithms
Authors: Li Bo , Liang Hongbin 
Published: November 2020

Abstract
The path planning method based on prior knowledge and Q-learning algorithm proposed in this paper solves the problems of low operating efficiency and slow learning speed in existing multi-robot coordination and collision avoidance. This method can be divided into two stages. Firstly, the improved Q-learning algorithm is used to plan the static collision free path of a single robot in the built model; After the Q-table is initialized with the prior knowledge obtained in the previous step, the Q-learning algorithm is used to achieve conflict-free motion among multiple robots. Finally, the simulation experiment shows that the proposed path planning method based on prior knowledge and Q-learning algorithm performs well in handling collision avoidance path planning of multiple robots.
High-speed Parallel Feature Extraction Algorithm of Wind Tunnel Image Based on GPU
Authors: Zhang Zhengyu , Xu Xiaochao , Yan Hua 
Published: November 2020

Abstract
In wind tunnel test, the serial feature extraction algorithm of wind tunnel image based on CPU is too slow to meet the execution speed requirements of wind tunnel test. To solve this problem, a high-speed parallel feature extraction algorithm of wind tunnel image based on GPU is proposed. The proposed algorithm is optimized in parallel from the CUDA kernel level and CUDA stream level to speed up feature extraction execution. In image pre-processing, a pixel is processed by a CUDA thread to achieve parallelization. In feature extraction, the image segmentation is introduced to parallelize 8-connected boundary tracking algorithm. And a CUDA thread is used to process an image block to parallelize feature extraction process. Furthermore, the proposed algorithm uses CUDA stream to asynchronous data transmission and data processing to achieve CUDA stream level parallelism. To verify the efficiency and effectiveness of the GPU-based algorithm, comparative experiment between CPU and GPU is conducted. The experimental results show that the performance of GPU-based parallel algorithm is far better than that of CPU-based serial algorithm. The GPU-based parallel algorithm can greatly improve the execution speed of feature extraction while ensuring the accuracy of feature data.
Research on Replacement Algorithm of Dynamic Page Storage Management
Authors: Zhao Yongchao , Xie Ying , Qin Haifei 
Published: November 2020

Abstract
This paper takes the dynamic page storage management in OS as the research aspect, and discusses the common three algorithms of FIFO, LRU and OPT. And put forward the idea of “vertically and horizontally”, use pseudo code to implement these three algorithm. Although the algorithm can be improved, but our idea of unifying the three algorithms is of great significance.
Dual Membership Fuzzy Support Vector Machine Algorithm Based on SVDD
Authors: Xu Yingcheng , Feng Wei , Pei Fei , Wang Haiyan 
Published: November 2020

Abstract
In the case of excessive overlap between positive and negative samples in data set, the deviation in the category of reconstructed sample points will lead to unsatisfactory discrimination of SVM, no matter what methods are used to reconstruct the sample set. A dual membership fuzzy support vector machine algorithm based on support vector data domain description was thus proposed, followed by a simulation analysis of common data set. Experimental results show that the proposed algorithm can work well in classification when the sample set is overlapped.
Image Stitching for Chest Digital Radiography Using the SIFT and SURF Feature Extraction by RANSAC Algorithm
Authors: Bakar Siddique Abu , Jiang Xiaoming , Gui Xiangfu , Li Guoquan , Li Zhangyong 
Published: November 2020

Abstract
Image stitching is one of the branches of computer vision. It combines two or more images for a scene to acquire a high-resolution panoramic image. An invariant local function often uses to stitch two images together. Since the flat plate of a digital radiography (DR) system does not cover all parts of the body, the whole bone structure image cannot seize in a single scan. To solved this problem, image stitching is broadly utilized by medical systems to stitch DR images, which can be helpful for scoliosis or lower extremity deformities in the diagnosis, and pre-operative planning are of great importance. In this paper, the stitching and retrieval of medical images planned. To conquer the background noise in medical images, and improve the recovery of quality and stitching rapidity of medical images, a random sample consensus (RANSAC) algorithm is useful to stitching the images of Chest digital radiography by scale-invariant feature transform (SIFT) and speeded-up robust features (SURF) feature extraction. Down-sampling utilizes to lessen the size of the images and reduction the measure of calculation. In the interim, the phase correlation is engaged to discover the overlapping region. After feature matching and perspective transformation, the stitched image is gotten dependent on the homography. At last, experimentation has finished showing the presentation.
Round-Trip Time and Available Bandwidth Estimation Based Congestion Window Reduction Algorithm of MPTCP in Lossy Satellite Networks
Authors: Yousuf Mohmmad Abu , Islam Md Mazidul , Hosen Md Shawkat , Ali Md Liton 
Published: November 2020

Abstract
A significant enhancement in recent communication systems is Satellite Communications. The performance improvement of the transmission control protocol (TCP) in satellite communications has been an active research area. Multipath TCP (MPTCP) ensures a robust solution than the regular TCP. However, the performance degradation in satellite networks due to the link asymmetry, high loss and high latency cannot distinguish the packet losses caused by network congestions from the losses properly. In this paper, a round-trip time detection-based algorithm is proposed using available bandwidth estimation (ABE) to mitigate the issue of blind decreasing of congestion window upon detecting the packet loss over lossy satellite networks. Experiments are done using the NS-2 network simulator to compare the various congestion control algorithms of both TCP and MPTCP over satellite networks. Simulations results from the experiments show that our proposed algorithm outperforms the existing algorithms which are mentioned in this article.
Research on Joint Distribution Route Optimization of Cold-chain Logistics for Fresh Agricultural Products
Authors: Yang Xuewen , Zhang Zhiguo , Wu You 
Published: November 2020

Abstract
In order to meet the development speed of cold-chain logistics, it is essential to enhance the efficiency of cold chain logistics, reduce the damage of fresh agricultural products, as well as guarantee the final transportation effect of all kinds of agricultural products. In view of the application of the Internet of things and the transportation principle of low temperature logistics, then the pattern of joint distribution is adopted, and the fixed cost, the transportation cost of distribution vehicles, the damage cost of fresh agricultural products and the operation cost of IOT are considered comprehensively. Under the basic setting of sufficient assumptions, the total cost to be lowest is taken as the objective function to construct a mathematical model to enhance the actual operation of cold-chain logistics in a scientific way.
A Method for Optimal Allocation of Regional Rail Transit Emergency Resources Based on Resource Sharing
Authors: Xu Lei , Wang Chuanjiang , Dong Wei , Sun Xinya 
Published: November 2020

Abstract
Regional rail transit is a composite rail transit system that includes multiple types of rail transit. Compared with single-standard rail transit, the types of risks increase, the risk impact is greater, and the consequences are more serious. Therefore, it is urgent to optimize the allocation of regional rail transit emergency resources to improve the overall efficiency of emergency operation and maintenance. Aiming at the characteristics of regional rail transit, this paper proposes a method for optimal allocation of regional rail transit emergency resources based on resource sharing. Firstly, according to the overall requirements of emergency services, the number of emergency stations is set, and then an emergency resource optimization allocation model for regional rail transit is built based on the p-median model. Secondly, through the multi-standard emergency resource sharing, the overall efficiency improvement of emergency operation and maintenance is achieved. Finally, a case study was carried out using Chongqing regional rail transit as an example to verify the effectiveness of the method.
Evolution Analysis of Zhuang Residences in Longan County, Guangxi
Authors: Zhao Mei , Zhao Xinghui , Gao Wei 
Published: November 2020

Abstract
Longan county, Guangxi province, China, is a region with a large population of Zhuang people, where Han culture and Zhuang culture communicate and collide frequently. A field survey was carried out in the villages of Longan county, and the architecture mapping of Zhuang residences were made. There are three types of Zhuang residences in Longan county successively: traditional timber Pile dwellings, secondary brick(stone)-timber Pile dwellings, and modern masonry structure ground houses. The characteristics of plan layout, important space, structure form and building materials of the three types of Zhuang residences are compared and analyzed, and the leading factors of the development and evolution of the three types of Zhuang dwellings are revealed.
Performance Analysis of Wireless Communication for High-speed Trains Based on SPN
Authors: Xie Yufei , Zhang Xubing 
Published: November 2020

Abstract
The quality of service high-speed train wireless communication is very important for high-speed railway operation. Modeling and simulation is an effective method to formulate travel plans and improve operational efficiency. In this paper, the SPN is used to establish a wireless communication model of a high-speed train for normal communication states and several system fault recovery states. The parameters are obtained through calculation, and the model is simulated and analyzed using TimeNet. The simulation results show that under the parameters required by the specification, the normal working probability of wireless communication is close to 100%, and the probability of several kinds of failure recovery is more than 95%, which meets the high reliability requirements.
Method for Identifying Global Structural Risk Bottleneck of Regional Rail Transit Based on Sensitivity Analysis
Authors: Li He , Dong Wei , Sun Xinya , Sui Tao 
Published: November 2020

Abstract
The characteristics of multi-standard rail transit systems coexistence of regional rail transit increase the risk probability of rail transit network. At the same time, the interaction between multi-standard systems and the integrity of the rail transit network increase the risk impact area and the risk consequences. Therefore, the risk bottleneck identification for regional rail transit is of great significance to realize targeted protection and optimization of key risk points and effectively reduce the global risk of the transportation system. In view of the fact that the existing risk assessment methods of rail transit network mostly use index fusion, which cannot reflect the global structural risk and cannot effectively evaluate the global risk bottlenecks of the rail transit network, this paper proposes a method for identifying global structural risk bottlenecks of regional rail transit based on sensitivity analysis. First, an assessment index for the global structural risk of the rail transit network is established, and then sensitivity analysis is used to assess the impact of the failure and optimization of station or section on the global structural risk of the rail transit network, so as to provide decision support for the protection and optimization of the rail transit network risk bottlenecks. Finally, the regional rail transit in Chengdu-Chongqing area is taken as an example to verify the effectiveness of the method.
Piggery Ammonia Concentration Prediction Method Based on CNN-GRU
Authors: Wang Kai , Liu Chunhong , Duan Qingling 
Published: November 2020

Abstract
The ammonia concentration in piggery has a great impact on the healthy growth of pigs and breeding environment. It is of great significance to control the ammonia concentration in piggery and ensure the healthy growth of pigs by timely mastering the ammonia concentration variation trend. In order to predict the ammonia concentration in piggery, a method based on CNN(Convolutional Neural Networks) and GRU(Gated Recurrent Unit) was proposed. Firstly, the environmental data in piggery and the meteorological data outside were collected, fused and preprocessed. Then, a piggery ammonia concentration prediction model combined with CNN and GRU was established. As a result, the ammonia concentration in piggery was predicted. The result shows that the proposed method has good prediction performance. The MSE (Mean Square Error), RMSE (Root Mean Square Error) and MAE (Mean Absolute Error) is 0.0637, 0.2524 and 0.1845, respectively. The proposed method can provide support for the early warning and regulation of piggery environment.
Study on Deformation Failure Mechanism and Control Measures of Toppling Slope
Authors: Zheng Huifeng , Wu Guanye , Chen Yi , Ju Nengpan 
Published: November 2020

Abstract
Aiming at the large range and depth of toppling and cracked deformation occurred in a typical toppling slope during the excavation in Miaowei hydropower station on the Lancang River, through geological survey, the classification standard system for toppling deformation rock has been established based on the main characteristic indexes of rock mass, and the mechanism of the toppling and tensile deformation of the slope at Miaowei is revealed. Comprehensive rescue reinforcement measures were implemented to control the development of deformation and to maintained the stability of the slope, which included prestressed anchorage and systematic drainage. Numerical simulation was implemented to predict the deformation and guide the reinforcement. The numerical and monitoring results both show that the deformation has been effectively controlled and the slope is already in a stable state with the completion of reinforcement measures. The study on the deformation mechanism and the successful practice of treatment of typical toppling slope in Miaowei hydropower station provide a constructive reference for similar complicated slopes.
Temporal and Spatial Characteristics of Climate Dryness in Eastern Qinghai Province
Authors: Jing Yuanshu , Cudemus Leila , Chen Xuejiao 
Published: November 2020

Abstract
Agrometeorological drought is the most important meteorological disaster that restricts the development of agricultural areas in the east of Qinghai Province. It is very important to evaluate the climate dryness by studying its temporal and spatial characteristics. Based on the long-term meteorological data of 12 meteorological stations, the temporal and spatial distribution of precipitation and dryness in the study area was analyzed. The dryness degree of each year varied greatly, ranging from 1.5 to 3.1, showing a trend of increasing with time. The dryness of the study area was relatively small in the three months of July, August and September, and larger in the period from November to March. The intensity of drought in the middle of the study area is higher than that in other areas, while the duration of drought in the south is longer. The drought tendency rate of the 12 weather stations was - 30.962/10a. The results help to provide reference for spring wheat planting to cope with spring drought.
Risk Assessment of Snow Disaster in Guoluo Prefecture of Southern Qinghai Province Based on GIS
Authors: Lv Chenqing 
Published: November 2020

Abstract
We evaluated snow disaster risk in 44 towns of Guoluo Prefecture by combining the methods of Analytic Hierarchy Process (AHP) and cluster analysis. Data were gathered from meteorological stations in Qinghai and Sichuan Provinces with GIS and RS tools. We considered snow depth, the duration of snow days, the area ratio of snow as three indicators for such evaluation, we can say Guoluo Prefecture is a higher hazard area of snow disaster. From the spatial distribution, we can see that the mild grade areas are Huashixia town in Maduo county, Zhalinghu village and Dongqinggou village, Lajia town in Maqin county; the moderate and minor severe grade areas are distributed basically in every county. And the minor severe grade areas cover almost every town in Dari county and Gande county However, the severe grade areas only distribute in Sanrima village, Tehetu village of Dari County and Dangluo village of Maqin county.
Face Recognition Based on Deep Learning of Small Data Set
Authors: Yu Lichun , Liu Jinqing 
Published: November 2020

AbstractFace recognition based on deep learning relies on large-scale label data, which limits the application of face recognition technology. To solve this problem, this paper proposes an improved VGGNet algorithm for face recognition. The improved algorithm requires less training data size, faster training speed, and the face recognition rate reaches more than 95%, which can meet the practical application requirements of most scenes.
An Hybrid Parallel Network Structure for Image Classification
Authors: Li Muhan , Jin Yijian 
Published: November 2020

Abstract
The image classification task is to divide certain image target into the specific class which they belong to. The deep neural network simplifies image classification by sending input image data into the neural network to learn feature extraction and having the output results automatically. Existing network structures have been able to achieve or exceed human capabilities in image classification tasks. However, these image classification technologies still have problems such as over-fitting network model, insufficient generalization abilities and long convergence time. Interference caused by complex environments may also cause the performance degradation. This paper proposes a hybrid parallel neural network structure for this kind of artificial intelligence task. By adopting the K-parallel connection CNN structure and using different scales of RNN/CNN structure mixed-layer modes, the effects of image’s size on different objects and different shooting angles can be reduced in image classification. Experiments on the datasets show that the proposed structure will have the advantage of accuracy and computational efficiency both in the validation datasets and the test sets.
Infrared Imaging Principle of the Front of the Vehicle
Authors: Zhou Zhen , Wang Yiwen , Gong Jianchun , Liu Lei 
Published: November 2020

Abstract
In recent years, with the progress of science and technology, infrared imaging is widely used in commercial and military, provide convenience for people’s life, the car in front of the infrared imaging improved the car in the way of low visibility in the form of security. Through the analysis of infrared imaging principle, this principle is applied to automobiles, and a simple infrared imaging system is designed for automobiles. This system is applied to the car to reduce the danger of the car in all kinds of bad environment and weather, and improve the driving safety of the car owner
A Study on the Composition and Communication of Chinese Character Images under the Context of Digital New Media
Authors: Liu Lin , Wang Yudi 
Published: November 2020

Abstract
Under the context of digital new media, the paper deals with the composition and dissemination of Chinese character images from three perspectives: the structure and communication of the character images, the presentation of character images and the modes of communication. Due to the computer technologies, Chinese characters could be presented on the screen with both pictures and sounds and become more intuitive and realistic. What’s more, the light effects and dynamic technique feature prominent in forming visual images of Chinese characters. In a word, the computer technologies help to realize the multi-dimensional and dynamic presentation of Chinese characters.
Geometric Drawing Method for Form-finding and Force-finding to Triangular Prism Tensegrity with End Surfaces not Paralleled
Authors: Shang Renjie , Zhao Yicheng , Yin Zhiqiang 
Published: November 2020

AbstractThe triangular prism tensegrity with arbitrary triangle bottom and end surfaces not paralleled is the most common type tensegrity structure. A geometric drawing method with four steps’ process for form-finding was given based on the properity of tensegrity structure, and the degree of freedom for form-finding was analysied. The force-finding method with ten steps’ process was given after form-finding, and the self-balancing internal forces was obtained by measuring the lengths of correspondant line segements. The geometric drawing method was carried out in CAD software by an example, and the example tensegrity structure obtained by the method was analysed by finite element method software, the correctness of the method was verified. The form-finding method is the geometric implementation of the force density method, and the process is intuitive and controllable, it is suitable and operational for triangular prism of tensegrity structures of any shape.
Alice: A LSTM Neural Network Based Short-Term Power Load Forecasting Approach in Distributed Cloud-edge Environment
Authors: Ding Zhengyang , Wang Jijun , Cheng Yiqing , He Chengxun 
Published: November 2020

Abstract
Load forecasting, as the baseline for decision-making, plays a key role in the management and control of the grid. Nevertheless, the rapid evolution of the smart grid has brought a dramatic increase in the volume of user-side data, traditional load forecasting approaches have to face the challenge of ensuring the accuracy of dynamic forecasting under the circumstance of the widespread application of big data. Meanwhile, the advance of the Industrial Internet of Things (IIoT) enables smart meters to acquire more plentiful data, which improves the accuracy of short-term load forecasting with appropriate utilization, but the gradual increase in the magnitude of data brought by IIoT technique has also left the computing equipment under great pressure. To address these challenges, in this paper, a Long Short-Term Memory(LSTM) network based short-term load forecasting approach deployed in the distributed cloud-edge environment, named Alice, is devised to deliver more precise results for the smart forecasting of power load. It adopts the LSTM network to perform the forecasting tasks and extends the whole system to the cloud-edge platform to implement parallel neural computing. Moreover, the Toeplitz Inverse Covariance-Based Clustering (TICC) algorithm is invited to enhance the efficiency of LSTM. Eventually, experimental evaluations on real dataset elaborate the superiority of the proposed Alice approach when compared to other state-of-the-art approaches.