bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis and Prediction of Pulmonary Tuberculosis Using an ARIMA Model in Shaanxi Province, China
Authors: Yang Cong , Yang Yali , Li Zhiwei , Li Yan 
Published: November 2020

Abstract
An analysis and prediction for the incidence of tuberculosis (TB) is particularly important since TB still has a high fatality rate in the world. However, this prediction is often influenced by inaccurate forecasting ways. We used data from 364,762 reported TB cases between January 2005 and December 2015 in Shaanxi Province, China. The known number of cases in 2016 was used to assess the accuracy of the model’s predictions. Through all aspects of analysis and comparison, the ARIMA (0, 1, 2) (0, 1, 1)12 were the most model. In the fitting dataset, for the ARIMA (0, 1, 2) (0, 1, 1)12 model, RMSE, MAPE, MAE and MER were 0.7667, 6.7810, 6.04944 and 0.06836, respectively; And in the forecasting dataset were 0.32808, 6.01834, 0.2899 and 0.0615, respectively. The model can predict the seasonal changes and trends of tuberculosis in the Shaanxi province’s population.
The Prediction of PM2.5 Concentration with an Intelligent Hybrid Model
Authors: Liu Xin , Zhang Xiaoxi , Zhao Xuejing 
Published: November 2020

Abstract
The objective of this work was to propose a hybrid model to predict the concentration of PM2.5 in three cities of China. PM2.5 is one of the most important pollution worldwide, therefore effective prevention and control are beneficial to human’s production and life. A hybrid model, CEEMD-MFO-SVR-GRA-BPNN, was proposed to predict the concentration of PM2.5. The proposed model is the combination of (1) complementary ensemble empirical mode decomposition (CEEMD) to decompose the original PM2.5 concentration data; (2) support vector regression (SVR) to give a regressed prediction model in which parameters was optimized via moth-flame optimization algorithm (MFO); (3) grey relational analysis (GRA) to select atmospheric factors with distinguished effect on PM2.5; and (4) back propagation neural network (BPNN) to reduce the forecasting residual. The hybrid model was evaluated in three cities, Guiyang, Lijiang and Guangzhou of China, in which the environments and geographical locations are different. The implementation of the proposed model and well-known CEEMD-MFO-SVR, CEEMD- WOA-SVR, EEMD-MFO-SVR, EMD-MFO-SVR and MFO-SVR, BPNN-meteorology models, were compared. The results show that the prediction of the proposed hybrid model is more accurate than the compared models.
Application of a Twin Model for Monitoring and Predictive Diagnosis of Calle Calle Bridge in Chile
Authors: Real J , Márquez M , Colomer E , Labrado M , Unión A 
Published: November 2020

Abstract
This study has developed a twin model tool that allows evaluating the current state and future behaviour of the Calle Calle bridge in Chile. The development of this twin model began with a finite element numerical model that was subsequently calibrated with data from sensors installed on the bridge. ANSYS APDL software was used to represent the structure by means of finite elements. The parameters captured by the sensors were the inclination and settlement in the abutments, the instantaneous deflection, and the proper frequencies. Calibration was an iterative process that sought to obtain a model that behaved similarly to the real structure. The twin model developed describes the reality of the structure allowing the simulation of future scenarios, thus improving the efficiency of management tasks, and thus achieving predictive maintenance. From the analysis carried out, it is concluded that the structure is in an acceptable state, requiring some maintenance. A great sensitivity of the bridge beams was also observed, which did not meet the current design criteria.
A Label-Enhanced Text Classification Model
Authors: Liu Yingjie , Liu Xueyang , Hu Wenhui , Zhang Long , Zhang Minghui 
Published: November 2020

Abstract
In the field of text classification, most of the previous work only uses one-hot labels, ignoring the correlations between labels. The paper proposes a novel label-enhanced text classification model, which utilizes the semantic correlation between sentences and category labels in the Natural Language Processing (NLP) classification task to integrate label information. We measure the similarity between instance and the category with the correlations among the labels. We test the proposed model on text classification tasks in two levels: text classification (document level) and sentiment analysis (sentence level). Experimental results show that the label-enhanced text classification model achieves great performance in multiple text classification tasks. In addition, experiment results on the unbalanced datasets show that our model is able to mitigate the impact of unbalanced data in classification tasks.
The Interactive Effect of Science and Technology Finance Development and Regional Economic Growth in the Yangtze River Economic Belt: Analysis Based on Panel Vector Autoregressive (PVAR) Model of Interprovincial Data
Authors: Shen Yiting 
Published: November 2020

Abstract
The interaction effects between science and technology finance development and regional economic growth have received academic and governmental attention in recent years. Based on the data of 11 provinces and cities in the Yangtze River Economic Belt from 2008 to 2017, this paper constructs a panel vector autoregressive (PVAR) model, and analyzes the direct and indirect relationship between Sci-tech finance input, Sci-tech finance output and regional economic growth through Gaussian Mixed Model (GMM) estimation and impulse response function. The study finds that: (1) The regional economic development level has a fluctuant effect on the support of science and technology finance development. (2) The enhancement mechanism of Sci-tech finance output is autonomous. (3) Sci-tech finance output and economic development level have a positive impact on each other. (4) Sci-tech finance output contributes more to economic development than Sci-tech finance input, and its effect is sustainable in the long run. Some practical proposals are put forward on the basis of the conclusions above.
Machine Learning Model for a Dynamic Path Planning Problem
Authors: Huu Thong Tran , Duc Duy Nguyen , Nananukul Narameth 
Published: November 2020

Abstract
Due to an advancement in Industry 4.0 technology, various autonomous systems have been developed in order to increase the operational efficiency. This paper considers an application of Industry 4.0 technology to an autonomous transportation operation. The paper focuses on applying a machine learning technique to a dynamic path planning problem where real-time randomized obstacle locations are considered. The routes or the solutions from the dynamic path planning problem are determined by an A-star algorithm, which are then used to build machine learning models based on an artificial neural network. The models were developed to discover the relationship between the input and output of the dynamic path planning problem. The structure of the network which is defined by the number of intermediate layers and the number of nodes is provided, where the overall accuracy is used to evaluate the setting efficiency. The proposed methodology was tested with a problem that consists of 7 types of paths, and the number of randomized obstacles fluctuated from 1 to 8. The paths were generated based on a layout of a consumer product warehouse. The proposed model succeeded in predicting the robot paths with 98.5% prediction accuracy.
Approximate Analytical Pricing of European Options under the Non-affine Stochastic Volatility Model
Authors: Yao Yuhang , Sun Youfa , Liang Xingyin 
Published: November 2020

Abstract
The non-affine stochastic volatility model has attracted increasing attention in recent years, due to its excellent performance in describing the nonlinear characteristics of asset price path. However, the fact that there is no close-form of option pricing formula under this model, restricts its use badly. To remove this restriction, two approximate analytical option pricing approaches are proposed in this paper, that is, the piecewise first-order Taylor expansion method and the perturbation-based asymptotic expansion method of implied volatility. The first method is used to derive an approximate characteristic function, then based on which the Fourier-Cosine expansion method calculates the European option price. In the second way, implied volatility of the European option price is asymptotically expanded around non-affine term of volatility. Compared with the existing methods in literature, numerical experiments show that the first method has higher accuracy, while the second method is of more practical significance. In addition, the accuracy of the first method is generally higher than that of the second method in most cases, while the second method performs better when the volatility is extremely small.
Mutation Information Extraction and Fluctuation Ratio Displacement Model of Step-like Landslides Based on Subdivided Monitoring Data
Authors: Liu Yuanxue , He Shaoqi , Yu Yongping , Cheng Xiang 
Published: November 2020

Abstract
The multi-source, massive and subdivided monitoring data provide powerful data support for revealing the causal mechanism of complex geological disasters and improving the accuracy of time prediction. Especially in the sub-monitoring period by day and hour, the relationship between displacement and factors is more complicated, and the hidden information is more abundant. In this paper, multi-point and large sample data of step-like landslides in the Three Gorges Reservoir area are used to extract landslide mutation and establish a displacement prediction model. Firstly, the standardization, the IR model and the kNN regression model were used to obtain the principal curve reflecting the common characteristics of the displacement in the region. According to the multiplicative model of displacement decomposition, the landslide displacement incremental signal was decomposed into the product of the fluctuation ratio and the trend displacement increment by FFT filtering method. Finally, by fitting the fluctuation ratio of principal curve, the displacement function model consisting of the induced factor term and the state factor term was obtained. Taking the daily monitoring data of four bank slopes in Fengdu County for nearly 3 years as an example, the result show that the model was more in conformity with the evolution of the step-like landslide by daily monitoring than other displacement prediction methods.
Research and Practice of “423 Mode” Teaching Based on Scratch Assisted Instruction——Taking the Java Programming Course as an Example
Authors: Sheng Wenwen 
Published: November 2020

Abstract
In the case of a general decline in the quality of students in vocational colleges, how to improve the teaching effectiveness of programming basic courses? This article introduces the use of graphical and Scratch software as teaching aids in the basic courses of higher vocational programming. At this stage, following two lines including Scratch and Java in the course design, and also following “423 model” consists of “pre-class”–“in class”–“after class” in the implementation of the classes to cultivate students’ innovative thinking ability, stimulate students’ learning interest, reduce the course difficulty and improving course teaching effectiveness. This teaching mode has achieved ideal teaching effect in Java teaching of Rizhao Vocational Technical College.
Simulations of Formation of Nanostructure in Silicon Surface by Single Slow Highly Charged Ion
Authors: Zhang Zhengrong , Li Huifang , Ma Yunyun , Luo Dan , Liu Zijiang , Lin Shumei 
Published: November 2020

Abstract
To understand the mechanisms of surface erosion induced by slow highly-charged ion (SHCI) bombardment, the surface nanostructure formation in Si (111) surface by single Xe44+ ion was studied by using molecular-dynamics (MD) simulations, based on analyzing the multiple electron emission of the substrate. The time evolutions of the temperature, energy, pressure and density of the substrate have been systematically studied. The results show the bombardment of the incident SHCI resulting in an explosive event in the surface. A shock wave propagating at ~104 m/s is formed in the system during the initial 175 fs. After this initial shock, many particles are ejected from the surface since the extreme non-equilibrium of the system. And at t=370 fs, a crater-like nanostructure with diameter of ~40 Å and depth of ~18 Å is formed at the incident site.
Relation Extraction using Language Model Based on Knowledge Graph
Authors: Xing Chengli , Liu Xueyang , Du Dongdong , Hu Wenhui , Zhang Minghui 
Published: November 2020

Abstract
Relation extraction is an important task in natural language processing (NLP). The existing methods generally pay more attention on extracting textual semantic information from text, but ignore the relation contextual information from existed relations in datasets, which is very important for the performance of relation extraction task. In this paper, we represent each individual entity as a embedding based on entities and relations knowledge graph, which encodes the relation contextual information between the given entity pairs and relations. Besides, inspired by the impressive performance of language models recently, we used the language model to leverage word semantic information, in which word semantic information can be better captured than word embedding. The experimental results on SemEval2010 Task 8 dataset showed that the F1-score of our proposed method improved nearly 3% compared with the previous methods.
Single-event Grey Target Decision Model with Vectorial Positive and Negative Bullseyes
Authors: Li Guangyu , Li Shoujun 
Published: November 2020

Abstract
Considering actual multicriteria decision-making problem can be decomposed into multiple single event grey target decisions, a novel structure of the grey target decision of singel event is proposed. In order to reduce the dimensionality, index effect evaluation values are assembled as objective effect evaluation value, which simplifies the complex decision-making problem by eliminating the index layer. Vectorial positive and negative bullseyes are defined followed by the definition of comprehensive off-target distance, which integrates the positive or negative off-target distance of the decision with the projection on the line through positive and negative bullseyes. Finally, an example for selection of green product supplier is studied to verify the effectiveness and feasibility of the single-event grey target decision model based on vector-type positive and negative bullseyes.
Numerical Simulation of Hydrodynamic Pressure on Concrete Bridge Pier in Water from a Series of Model Tests
Authors: Qin Yifang , Tao Xiaxin , Liu Haiming , Tao Zhengru 
Published: November 2020

Abstract
To develop numerical procedure to simulate hydrodynamic pressure on concrete bridge pier in water, finite element models are built by software ADINA with the same sizes and material properties in a set of shaking table tests in this paper. The results our numerical simulations show that the all pressures on the three piers decrease with the submerged depth at the similar rate as test data shows, and the mean values of the ratios of numerical results to the test data are mainly from 0.8 to 1.0. The pressures on piers with different section shapes at same depth are varied and the relative order is not stable. The finding is similar to that from the test data, but different to the shape coefficient values provided in some seismic design codes of highway bridges. It suggests to check what kind of horizontal variation of hydrodynamic pressures at same depth level is there from the center to the edges. The pressures with reflected wave are approximately half to two third of those without reflected wave. It means that the reflection effect reduce the hydrodynamic pressure on bridge pier obviously. The effectivity of the absorbing stuff on the side walls of the tank in the tests must be improved, or a new way to replace this kind of measure must be worked out.
Numerical Simulation of Hydrodynamic Condition on Shielding Measures of Hong Kong-Zhuhai-Macao Bridge
Authors: He Jie , Zhao Xinsheng 
Published: November 2020

Abstract
According to the characteristics of water flow movement in the junction area of island and tunnel, the “asymmetric” type double diversion dike measures for the north and south sides of basement shelter area were formulated. The 3D mathematical model of flow in the water area of local sinking base was established in this article. The hydrodynamic simulation of the diversion dike was carried out. The results showed that the flow velocity in shelter area of basement is greatly reduced. The maximum flow velocity of artificial flattening section of E33 pipe joint base is less than 0.5 m/s, and the maximum flow velocity of flattening ship construction section is not more than 0.8 m/s. The flow rate can meet the conditions of immersed tube installation. For safety reasons, E33 pipe joint placement time is suitable for the small tide period with weaker power flow.
Numerical Simulation of Straight Rib Solar Air Collector
Authors: Yi Xiaofang , Gu Weili , Man Xuepeng 
Published: November 2020

Abstract
In this passage, a straight rib solar air collector is proposed. The effects of the number of ribs, the height of the ribs, the length of the ribs and the air inlet velocity on the heat collection efficiency and the normalized temperature difference are studied using the orthogonal test method. The orthogonal test plan with 4 factors and 3 levels is selected to perform numerical simulations on different collector models. The results show that the significance of each orthogonal factor on the heat collection efficiency and the normalized temperature difference is: Inlet velocity> Height of ribs > Number of ribs> Length of ribs, and get the best parameter combination: the number of ribs is 9, the rib height is 45mm and the rib length is 2000mm. In addition, the study found that the average heat collection efficiency and normalized temperature difference of the model are 3.98% and 0.00052 (K·m2)/W higher than the ordinary solar air collector.
Rolling Process Analysis of Working Rollers of Cold Rolling Mill Based on ANSYS
Authors: Shi Kun , Zheng Gang , Hang Jianhua 
Published: November 2020

Abstract
Aiming at the complex changes of the working rollers and rolled pieces in the rolling process of a cold rolling mill, this paper built a finite element model of the working rollers and rolled pieces based on ANSYS, and analyzed the rolling process of working rollers by using the transient algorithm of structural dynamic equation. The stress-strain situation and rolling force curve of working rollers and rolling pieces were obtained, The results revealed the characteristic change process of working rollers and rolled pieces in the rolling process, which layed the foundation for further realizing the precise control of the rolling process of cold rolling mill.
Empirical Analysis of Stock Investment Based on β-KFCM
Authors: Wang Yuxue , Song Zongxiang , Ren Xiaoping 
Published: November 2020

Abstract
Cluster analysis is an analysis method that classifies data sets. It measure the similarity between different data and classifies them on the basis of similarity, but the classification is unknown. In recent years, with the popularization and improvement of information technology, a large number of diversified data have been produced in various industries. In order to extract data features and classify them, this paper, based on the study of fuzzy C-means clustering algorithm, take the systematic risk coefficient as the weight, expand the model to get the weighted fuzzy kernel clustering algorithm: -KFCM fuzzy clustering algorithm and solve the algorithm. Based on the empirical research, we choose six Accounting Indicators to study 50 stocks in A-share market, including current ratio, cash ratio, year-on-year growth rate of operating revenue, return rate of total assets, net sales interest rate and asset liability ratio. According to the empirical research, we can get the results that the investment grade is divided into three categories, among them, Category I is the recommended high-quality investment variety, category II and category III are next to it.
Study on the Constructing and Developing Mode of the Smart Port in the Beibu Gulf of Guangxi
Authors: Cheng Zilai , Wu Haibin , Ni Peng 
Published: November 2020

Abstract
In order to form a new constructing and developing mode under the background of the deep integration of the traditional port and the modern information technologies, the Beibu Gulf Port Group in Guangxi will focus on the three core themes which are the intelligent control, the digital supply chain and the “Internet + port” information services, to carry out the smart port construction. Aiming at studying the constructing and developing mode of the construction of the smart port in the Beibu Gulf, its constructing objectives were clarified, the overall technical framework was built, the system constructing plans were put forward, and the expected effects were analysed. On the whole, the Beibu Gulf Smart Port will realize the intellectualization, automation and platform construction of the group ports, help the transformation and upgrading of “intellectualization” of the ports, and create a new smart port ecosystem of “resource integration and optimization, business cohesion and coordination, information interconnection and interoperability” in the Beibu Gulf region. The construction of the Beibu Gulf smart port can also play its leading role in the regional economy better, and provide strong support for promoting the development of the Beibu Gulf Economic Zone and the opening and development of Guangxi.
Research on Music Education Model by Using Computer Music Technology in Colleges
Authors: Zhou Yang 
Published: November 2020

Abstract
Against the background of new teaching conditions and the rapid development of computer technology, computer music technology serves as the important method in modern music teaching. The object of this article is to have a study of the methods and models of university music education under the reform of technology in computer music. In this article, students majoring music majors and non-music majors of the Art University are the subject of the survey. They are divided into professional classes (N=50) and non-professional classes (N=50). The professional classes use computer music technology for practical teaching, and Non-professional classes use traditional music to teach. After the experiment, the degree of mastery of the music professional knowledge of the two classes and the acceptance of computer music teaching and traditional music teaching methods were investigated and analyzed. The results of the study show that the introduction of computer music production technology can motivate students to participate in learning, allowing students to experience the charm of music and enrich the content of music knowledge in an intuitive and vivid situation.