bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hyperspectral image classification based on multiscale convolutional network
Authors: Ju Yi 
Published: June 2021

Abstract
Hyperspectral Image (HSI) classification is an important task in the field of Hyperspectral Image processing. However, the existing classification methods unable to solve the problems caused by hyperspectral image information redundancy, insufficient image feature utilization and Hughes phenomenon. Aiming at these three problems, a hyperspectral image classification algorithm based on deep learning is proposed. The Multiscale Convolutional Neural Network (MCNN) was used to excavate deep features and realize the learning of multiscale features. Then, the features of different scales were fused and classified. The results show that the proposed algorithm has higher classification accuracy than the traditional ones. Also, it has strong generalization ability and robustness. The effectiveness and feasibility of the proposed algorithm are fully verified.
A Method of Blood Vessel Segmentation in Fundus Images Based on Image Enhancement
Authors: Tao Juliang 
Published: June 2021

Abstract
The changes of retinal vessel width are the key steps in the accurate diagnosis, early treatment and surgical planning of ocular diseases. The segmentation of retinal vessel is the basis of computer-aided diagnosis and large-scale disease screening. In this paper, we propose an algorithm for segmentation of fundus image based on image enhancement. At first, the ocular fundus image is enhanced by Laplacian pyramid, and the enhanced image vessel is more obvious than the background. Then, an improved matching filter algorithm is used to segment the ocular fundus image vessel. Experimental results show that the proposed method is more accurate than the traditional segmentation method. And it has strong robustness to the fundus images under different illumination conditions.
The application of discrete mathematics to microeconomics
Authors: Tao Lina , Cheng Jiaxing 
Published: June 2021

Abstract
Mathematical logic is one of the two cornerstones of discrete mathematics course, which uses mathematical methods to study the relationship between the premise and conclusion in reasoning. Microeconomics is the study of individual economic units, how market mechanisms work and function when resources are scarce, and ways to improve their functioning. Game logic is a new direction in the field of logic game theory is mainly applied to behavioural theory in microeconomics. This paper studies the combination of logic and game theory from the propositional logic in mathematical logic.
Kernel-lasso feature expansion method: boosting the prediction ability of machine learning in heart attack
Authors: Dai Zongrui , Jiayi Li , Gong Taowen , Wang Chenfei 
Published: June 2021

Abstract
Heart attack needs to cause a high degree in modern society, which is now at the top of the list of most common diseases. One-third of all deaths in the world are caused by heart disease, and in our country, hundreds of thousands of people die of heart disease every year. If people can predict heart attack at an early period, they may prevent and cure the potential risk. Therefore, one novel and efficient prediction model is needed. Based on machine learning, we design one novel method in feature selection called kernel-lasso feature expansion to increase the prediction ability. This method considers the potential influence by the curse of dimension and lack of features, which can increase the dimension of the existed data and select the effective features by lasso regression. Compared with other feature selection methods such as Lasso and step regression, the novel method increases the predicted ability of gradient boosting machine, DNN, and SVM models, while SVM with kernel-lasso feature expansion achieves the best performances in Accuracy (0.84(%95Cl:0.78-0.89)).
Analyzing the current status of global 5G research from the perspective of bibliometrics
Authors: Mao Yuanyuan 
Published: June 2021

Abstract
In order to fully understand the current research status in the field of 5G technology, using 5G documents included in the WOS?Derwent Innovations Index as the data source, this article conducts a bibliometric analysis of “5G technology” from multiple dimensions such as the number of publications, countries, institutions, and patents. Through the CiteSpace software, the scientific knowledge map in the 5G field is drawn, and the research overview in the 5G field is obtained, scholars in this field can make theoretical references in further research.
A new method for judging the stability and boundedness of continuous-time fractional positive systems
Authors: Yang Lijuan 
Published: June 2021

Abstract
By decomposing the state matrix into a symmetric part and an antisymmetric part, this paper investigates the stability of continuous-time fractional positive systems, and a sufficient and necessary condition for continuous-time fractional positive systems to be bounded in a given interval is obtained. The results show that when the system corresponding to its symmetric part is asymptotically stable, continuous-time fractional positive systems is also asymptotically stable.
Research on multi feature fusion perception technology of mine fire based on inspection robot
Authors: Miao Kebin , Ma Jian , Li Zefang , Zhao Yunlong , Zhu Wenshuo 
Published: June 2021

Abstract
In order to improve the real-time and accuracy of mine fire identification, based on the summary of the existing fire monitoring methods, a mine fire early warning model based on patrol robot and multi-sensor and image recognition is proposed. The video image is obtained by using the high-definition camera of inspection robot, and the flame suspected area of video image is obtained by combining frame difference and background difference after filtering. The improved three scale analytic hierarchy process is used to fuse the circularity feature, sharp angle feature, centroid movement feature, color feature and area growth feature of the flame suspected area image to obtain the flame result. The three-frame difference method is used to binarize the smoke video image, and the smoke texture feature, smoke motion feature and smoke color feature are extracted to recognize the smoke image. The improved three-scale analytic hierarchy process (AHP) is used to fuse and judge the smoke in the combination of infrared thermal imager temperature measurement and smoke sensor. Inspection robot uses unified detection standards and intelligent analysis technology to sense mine smoke and flame. This method can improve the real-time, accuracy and robustness of mine fire perception.
An Empirical Analysis of the Bidirectional Dynamic Effect between Financial Competition and Industrial Agglomeration
Authors: Wang Zhengyu , Pang Ran , Cai Defa 
Published: June 2021

Abstract
This paper uses the data of 30 provincial-level panel in China to establish a dynamic panel simultaneous equations model. The system generalized moment estimation (sysgmm) and three-stage least squares (3SLS) are used to estimate and test the robustness of the model, respectively, to study the relationship between financial competition and industrial agglomeration. The results show that: (1) there is a bidirectional causal relationship between financial competition and industrial agglomeration. Financial competition through preferential policies to encourage technology research and development, resulting in technological innovation spillover effect to attract industrial agglomeration, but the effect is not good, and industrial agglomeration will also encourage finance to increase the competitiveness; (2) the bidirectional effect has time lag, the early financial competition and industrial agglomeration In order to have an effect in this period. All of conclusions above have important implications for changing the mode of financial competition and improving the quality of industrial agglomeration.
Research on Embedded Navigation System of Agricultural Robot Based on ARM
Authors: Wang XiaoJian , Hou Xujie , Niu Wenhuan , Jiang Shaoyan 
Published: June 2021

Abstract
This paper takes agricultural robot as the research object, combines machine vision and embedded technology, proposes an embedded agricultural robot image processing and path navigation algorithm based on machine vision, and successfully transplants the image processing and path navigation algorithm to the embedded environment based on ARM9.
User Experience of Loading Design: the Influence of Different Presentation Duration and Type on Time Perception
Authors: Hou Danni , Yao Kang 
Published: June 2021

Abstract
This study simulates the situation that users are required to wait when they encounter a buffer when watching online video, and investigates the influence of the duration and type of loading on time perception. The task was to estimate the perceived loading time. Results (1) the accuracy of time perception decreased with the time of loading. (2) the type of loading is related to time perception. The larger the amount of information contained in loading, the shorter the time perception of viewing video. (3) there is interaction between the duration of loading presentation and the type of loading. The results show that the amount of information and waiting time are related to time perception.
Study on the Construction of Curriculum System for the Integration of Environmental Design Courses and Certificates in Colleges Based on Statistical Analysis
Authors: Guo Lingling , Zhang Lipeng 
Published: June 2021

Abstract
With the start of the pilot work of the 1 + X certificate system in China, the education department began to encourage college students to strive for the corresponding vocational skill level certificate on the basis of obtaining the academic certificate, so as to improve the employment situation and alleviate the current social employment difficulties. In this paper, the environmental design professional courses in Colleges and universities as an example, in-depth analysis of the shortcomings of the current single teaching environmental design professional course system, through the statistical analysis of the questionnaire of college students and enterprises, the feasibility of realizing the integration of environmental design professional teaching course certificate under the experimental conditions of “1 + X” certificate system in Colleges and universities is studied, and the corresponding curriculum system is constructed. The statistical results show that when the curriculum system of environmental design is adopted, the satisfaction of students and enterprises has increased. The results show that the integration of academic education and vocational skills training can be achieved by setting up the course of “course certificate integration”, which is helpful to cultivate a large number of students who meet the needs of enterprises and improve the employment rate of college students
An elevator passenger behavior recognition method based on two-stream convolution neural network
Authors: Lan Shengnan , Jiang Saihua , Li Gang 
Published: June 2021

Abstract
In order to reduce elevator accidents caused by passengers’ incorrect use, a method for elevator passenger dangerous behaviour recognition based on two-stream convolutional neural network is proposed after analysing existing elevator passenger behavior recognition methods. A two-stream convolution neural network model framework and its parameters for elevator passenger behavior recognition are also given. Herein, the appearance features of human behavior are extracted from space domain, and the motion features of human behavior are extracted from time domain. Finally, the softmax outputs of the two-stream are merged with the liner weighting to realize human behavior recognition. The model is trained and evaluated on the video dataset of elevator passenger behavior. The results show that this method can be used to identify the unsafe behavior of elevator passengers, and the average recognition rate is 96.87%.
Method for detecting surface defects of runner blades of large hydraulic turbines based on improved real-time lightweight network
Authors: Liu Cheng , Su XinYi , Wu Jialing , Zhou Qun , Li Tao , Tian Tang , Li XianYong , Hu GuiChuan 
Published: June 2021

Abstract
Cavitation erosion, wears and cracks caused by residual thermal stress occur during the operation of hydropower units. It is a key scientific problem that needs to be solved urgently to detect defects in the foundation pit of hydropower units. In this paper, a mobile robot is used to obtain the surface image of the over-current parts of hydropower units, and deep learning algorithm is used to detect defects. In order to detect blade surface defects more safely, reliably, efficiently and quickly, this paper proposes an improved real-time lightweight convolutional neural network MobileNetv3-YOLOv4-Lite, which is suitable for portable embedded devices. In this paper, MobileNetv3 is selected to replace CSPDarkNet53 as the new backbone extraction network, and all standard convolutions are replaced by depth separable convolutions. Compared with CSPDarkNet53, MobileNetv3 only needs 37.35MB in weight, which is 206.94MB lower. It shows that the network proposed in this paper has the advantage of low memory and can run on CPU. The defect detection accuracy of MobileNetv3-YOLOv4-Lite can reach 97.48%, and the GPU can process 3024x4023 images, which can process 44 images in one second. The standard convolution of the enhanced feature extraction layer network is replaced by the depth separable convolution, and the parameter quantity is reduced by 29.33%. Therefore, it can be considered that the real-time lightweight convolutional neural network MobileNetv3-YOLOv4-lite proposed in this paper can detect the surface defects of turbine blades well.
Detecting and Classifying Self-Admitted of Technical Debt with CNN-BiLSTM
Authors: Zhu Kuiyu , Yin Ming , Li Yizhen 
Published: June 2021

Abstract
Technical debt expresses the use of non-optimal solutions for short-term gains. Self-admitted technical debt is a technical debt that is deliberately introduced and recognized by developers in source code comments, including design debt, requirement debt, and defect debt, etc. Currently, many methods are proposed to detect SATD. However, these methods are limited to the identification of SATD or non-SATD. In this paper, we propose a CNN-BiLSTM method to detect and classify SATD. Through our cross-project experiments on 10 projects, it is shown that our method can not only effectively detect SATD, but also classify design debt, requirement debt, and defect debt in SATD.
A study on optimal dispatch of meical resources under the situation of COVID-19
Authors: Yang Yingrui 
Published: June 2021

Abstract
In order to improve the efficiency of production, transportation, storage and use of medical resources under COVID-19 pandemic, we propose a simplified model for medical resources supply chain management by mathematical programming. Based on the reserve and demand of medical resources in a given area, the proposed model provides daily real-time transportation decisions and expansion decisions of hospitals, factories and warehouses under epidemic situation by analysing factors such as different regions, duration, factory capacity, warehouse reserves, hospital demand, transportation and expansion costs of factories, warehouses and hospitals. The promo package of Python language is used to formulate a mixed integer linear programming model. In this model, under the conditions of meeting the demand of medical resources in the case of slow development and sudden outbreak of epidemic situation, a commercial solver, CPLEX, is able to provide the solution for each situation with the lowest supply cost within one second CPU time. This model provides a feasible scheme for further solving the complicated forecasting and planning of medical resources dispatch under the situation of pneumonia in COVID-19.
Analysis of an epidemic model with latent infection
Authors: Liu Wenjuan , Chang Zaibin , Qiao Yaqin 
Published: June 2021

Abstract
An infectious disease model with latent infection is studied, and the basic reproductio n number of the model is obtained When the basic reproducing number is less than 1, the mode l has only one disease-free equilibrium. When the basic reproducing number is greater than 1, t he disease-free equilibrium is unstable. The model also has a unique positive equilibrium. The global asymptotic stability of the two equilibria is analyzed by linearization method, Liapunov function method and geometric method.
Research on the impact of 5G technology on teaching behavior
Authors: Xue Jianting , Mao Yuanyuan 
Published: June 2021

Abstract
Affected by the COVID-19, the opening of higher education institutions in China has been postponed, and the policy of “suspending classes without stopping” has become a litmus test for emergency response to the epidemic and for education informationization. Under this opportunity, the online teaching model has risen rapidly and has become a hot spot for teaching reform. This article explains the development process from traditional teaching to smart teaching, and the shortcomings of online teaching at this stage. On this basis, with the new generation of communication technology 5G as the background of the times, the future teaching is prospected from the aspects of AI teaching, holographic interactive classroom, and virtual technology teaching.
Mountaintop mining legacies constrain ecological, hydrological and biogeochemical recovery trajectories
Authors: Ross Matthew R V , Nippgen Fabian , McGlynn Brian L , Thomas Christian J , Brooks Alexander C , Shriver Robert K , Moore Eric M , Bernhardt Emily S 
Published: June 2021

Abstract
Mountaintop mining, like all forms of surface mining, fundamentally alters the landscape to extract resources that lie 10–100 ms below the land surface. Despite these deep, critical zone alterations, post-mining landscapes are required by United States law to be restored to ecosystems of equal or greater value than the ones they replace. Yet, remote sensing of vegetation across more than 1000 km2 of reclaimed surface mines in WV, USA reveals little evidence that these habitats are returning to the diverse Appalachian forests that were removed by mining. Instead, even decades after reclamation, mined landscapes are dominated by shorter and sparser trees. Based on detailed field studies and literature synthesis, we suggest that part of these widespread failures in re-establishing native forest result from the fundamental changes in critical zone processes on the post-mining landscape. Former surface mines have substantially altered topography, hydrology and chemistry. In these post-mining, synthetic landscapes, water moves more slowly through piles of exploded bedrock, changing the system from one dominated by stormflow in unmined catchments, to one dominated by baseflow after mining. This slow-moving water, travelling through high surface-area debris and pyrite-rich bedrock, creates ideal conditions for highly elevated weathering in mines both old and new. These foundational changes to the critical zone set ecosystem recovery along a novel trajectory, in which the legacy of past disturbance is likely to constrain the establishment of native forest for many decades.
Study on Mechanical Properties of Concrete-Filled Aluminium Alloy Tube Column under Lateral Impact
Authors: Yantao Jiang , Peiding Wang , Chuanyun Xiong 
Published: June 2021

Abstract
Concrete-Filled Aluminium Alloy Tube (CFAAT) column may be damaged by lateral impact. Based on general finite element analysis software, the dynamic analysis and performance of lateral impact of CFAAT columns with different tube wall thickness are studied in this paper. The results show that when the outer diameter of the columns is constant, the impact resistance of the columns can be improved by increasing the thickness of the aluminium alloy (Al alloy) tube, and the reinforcement of the core concrete constraint by increasing the strength and thickness of the Al alloy tube is the main reason for the enhancement of the impact resistance.
Research on Foundation Pit Monitoring and Management System Based on BIM+GIS+IOT
Authors: Chuang Gu , Yiqun Chen , Zhongmou Chen , Peng Li 
Published: June 2021

Abstract
Since traditional foundation pit monitoring methods cannot meet the overall safety requirements of engineering, a foundation pit monitoring and management system based on BIM+GIS+IOT was proposed in this paper. BIM, GIS and Internet of Things were applied in the system. ESP32 chip and ESP-IDF framework were used to develop the IOT to complete the real-time collection and transmission of monitoring data, and the BIM and GIS model data is integrated and displayed by linking the information of the monitoring points and BIM model. The system then is used in the construction of a subway station foundation pit for environmental monitoring and early warning monitoring.
Elastoplastic analysis of Kunshan Xintiandi super high-rise office building under earthquake
Authors: Zhang Xiaomeng , Liu Ziao , Yang Xiao , Zhou Yilun , Ren Qingying , Liu Wenting 
Published: June 2021

Abstract
Kunshan Xintiandi Super Tall Building is 142 meters high, with 3 floors underground and 31 floors above ground. Its structural system is composed of concrete-filled steel tube frame and core tube. The elastoplastic time-history analysis of the building was carried out by using PKPM-SAWS to analyze the overall overall index of the whole structure under large earthquake, and the mechanical performance of the key components under large earthquake was analyzed, and the loss mechanism of the key components under large earthquake was obtained, so as to ensure the mechanical performance target of the super high-rise building under large earthquake are not bad.
Research on European Container Ports Based on Lotka-Volterra Model
Authors: Xu Yiwen 
Published: June 2021

Abstract
Europe is one of the important regions with the global container shipping business. Studying competition among port container business helps to improve the overall containerized transportation efficiency in Europe and assist liners to make correct decisions under the new global shipping pattern. Therefore, this paper uses non-autonomous Lotka-Volterra model to quantitatively study the type and degree of competition among major European container ports. The result shows that the ports in the Mediterranean region tend to be predatory and competitive. Besides, this paper also predicts the future trend of competition and cooperation of European container ports under the scenarios of “Sulphur Restriction Order” by modifying the utility function.
Layout analysis and optimization design for Zhengding Bus Terminal
Authors: Li Yanwei 
Published: June 2021

Abstract
As an important component of road transportation, the bus terminal has always been the focus of research. Therefore, this article uses a combination of quantitative and qualitative analysis to study Zhengding third-level bus terminal from the perspective of layout analysis. On the basis of actual investigation, the relevant indicators of the bus terminal scale are calculated. At the same time, the analysis of the three functional areas and process flow lines inside the passenger station revealed that the passenger station has the problems of intersection of pedestrians and vehicles and the unreasonable and imperfect layout of the ticket waiting hall. Finally, a specific optimization plan is proposed and optimized for the problems existing in Zhengding bus terminal.