bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Integrated Development of Ice and Snow Industry and Health Industry——Take Genhe City and Tieli City as examples
Authors: Li Miaomiao , An Yonggang , Huo Pengfei , Zhang Lisheng 
Published: November 2020

Abstract
With the rapid development of modern society and economy, people’s pursuit of health is becoming more and more comprehensive, involving all aspects of material and spirituality. However, the ice and snow industry and the health industry are closely related social and economic phenomena, and the integration of the two is gradually increasing.[1]In recent years, various tourism activities such as ice and snow tourism, health tourism, and adventure tourism have become a necessary choice for people to return to nature, get close to nature, and pursue a healthy life. This article takes the integrated development of ice and snow industry and health industry in Tieli City and Genhe City as an example. Discuss the necessity and basic conditions for the integrated development of the ice and snow industry and the health industry and initially designed the “ice and snow + health” product system.
Fault diagnosis of photovoltaic array based on SE-ResNet
Authors: Fu Shaofeng , Cai Fenghuang , Wang Wu 
Published: November 2020

Abstract
In recent decades, fault diagnosis of photovoltaic (PV) arrays has become more and more important for the power generation of PV systems. Many traditional artificial intelligence methods have been successfully applied to use fault data samples to build fault diagnosis models, but most rely on manual feature extraction or expert knowledge to build diagnosis models, which is inefficient and may ignore some potentially useful features. Therefore, this paper proposes an SE-ResNet PV array fault diagnosis algorithm based on Residual Network (ResNet) and Squeeze-and-Excitation Network (SENet), and uses Bayesian Optimization (BO) optimize the parameters. In order to verify the effectiveness of the proposed fault diagnosis algorithm, a comprehensive fault experiment was carried out on the PV platform. Experimental results show that the model has achieved high overall performance in terms of accuracy, generalization performance, reliability and training efficiency, and has high practicability.
The Comparative Study on Underlying Features of PainingTang-ka Images and Natural Images
Authors: Zhang Weijiang , Dang Hongshe 
Published: November 2020

Abstract
Our purpose was to find the difference between the color features and texture features of natural images and painted Tang-ka images. Taking natural images as a reference, painted one were analyzed in HSV color space. The natural image and painted Thang-ga texture features were extracted, using the Tamura’s method. The data showed that the natural image’s coarse was larger than the painted Tang-ka, and painted Tang-ka were more saturated than natural images. Compared with natural images, the painted Tang-ka’s directonality has higher value. By contrast, the red Tang-ka had a higher value than the golden one.
Long-distanceinfrared video pedestrian detection using deep learning and backgroundsubtraction
Authors: Zhu Yaling , Yang Jungang , Xieg Xiaokai , Wang Zhihui , Deng Xinpu 
Published: November 2020

Abstract
Infrared video-based pedestrian detectionplays an important role in surveillance and automatic driving. Compared with vision cameras, infrared cameras have the characteristics of all-day and all-weather availability. The current infrared video detection methods generally follow the traditional paradigm. However, when objectsare at a long distance, it is challenging for existing methods to achieve accurate detection. Meanwhile, deep learning-based methods have been widely used in visible light object detection. In this paper, we introduce an algorithm which combines deep learning and background subtraction methods to achieve infrared pedestrian detection. Firstly, background subtraction method is performed to provide the inter-frame information for the deep learning module. Secondly, the RefineDet equipped with an attention module is used to improve the detection accuracy for small pedestrian. Moreover, we develop a novel infrared video dataset which includes long-distance pedestrian for performance evaluation. Experiments demonstrated that our method can achieve a superior performance as compared to RefinDetand SSD methods.
Z-Net: A Novel Way of Lane Detection
Authors: Zhang Ziyuan 
Published: November 2020

Abstract
In this paper we proposed a new neural network Z-net for lane detection. The novelty of this network is not the network itself but the detection method. After comprehensive investigation and analysis of the application of several used networks in lane detection, we analyzed the advantages and disadvantages of various networks and modified the existing network to get the Z-net. Under the influence of rapid development of lane detection, it is necessary to propose a neural network with fast detection speed and great accuracy. We found out that Z-netsatisfies these two requirements very well.
Study on academic Early Warning System for Information Engineering Vocational students
Authors: Luo Jing 
Published: November 2020

Abstract
Due to the expansion of higher vocational college enrollment, the different quality of students and the high quality requirements of enterprise talents, this paper proposes an academic early warning system for higher vocational college students, which can be used for the early warning of students’ performance and improve the teaching quality. Firstly, the clustering algorithm is analyzed, and the parallel K-means algorithm is adopted in the general algorithm. During the startup and running of the program, the processing time of the algorithm is short and the total consumption of the system is small. Compared with the existing data mining technology, parallel K-means algorithm has good practicability and flexibility.
Real TimeDetection and Tracking Method of Pilot’sHeadPositionBased on MTCNN-DeepSORT
Authors: Zhang Limin , Jiang Jie , Fang Wei , Liu Kai 
Published: November 2020

Abstract
In view of the problems of the traditional head detection and tracking technology in pilot cabin simulation training, such as low precision, poor real-time performance and easy to be interfered by the outside world, we propose a head detection and tracking method based on MTCNN-DeepSORT combined with deep learning method. Firstly, the continuous video images in the cockpit are preprocessed by computer vision, and then the processed images are extracted by convolution neural network to detect the face. At the same time, the facial feature points are marked. Through the spatial coordinate calculation of the obtained facial feature points, the pilot’s head posture angle is obtained, and then combined with DeepSORT tracking algorithm can track the pilot’s head continuously and in real time, and finally complete the detection and tracking of pilot’s head position. The experimental results show that the method based on MTCNN-DeepSORT has higher detection accuracy, better real-time performance and stronger robustness than the traditional methods.
Research Summary on Light Field Display Technology Based on Projection
Authors: HaiyangYu  , XiaoyuJiang  , XingpengYan  , Yan Zhiqiang , Wang Chenqing , Yan Zhan , Wang Fenghao 
Published: November 2020

Abstract
In recent years, three-dimensional display technology has developed rapidly, among which light field display technology is a type of technology with broad application prospects that can realize naked-eye stereo display. With the enhancement of digital image processing capabilities and the development of projection technology, projection-based light field display technology has also made great progress. This article analyzes the principle and development of light field display technology based on high-speed projection and projection arrays, briefly introduces the relevant experimental results of the research team at home and abroad, and finally discusses the application prospects of different technical directions.
A TSP algorithm based on link degree
Authors: Yu Guyang , Shi Huajun 
Published: November 2020

Abstract
The fundamentality of the traveling salesman problem (TSP) is the choice of an edge in the next step. This paper proposes a concept of link degree, which can display the potentiality of an edge to belong to the shortest Hamiltonian cycle in a more effectively manner and, on this basis, it presents a greedy algorithm for the TSP. Meanwhile, some relevant theorems and conjectures as well as some problems triggered are discussed as well.
Short-term Traffic Flow Prediction Based on Harmony Search Algorithm Optimized Wavelet Neural Network
Authors: Shen Guifang 
Published: November 2020

Abstract
ln order to improve the prediction accuracy of urban road short-term traffic flow, this paper proposes a short-term traffic flow prediction model of wavelet neural networkoptimized by harmony search algorithm(HS-WNN),to solve the problem of slow convergence speed and local optimization when the traditional wavelet neural network one-way gradient descent method is used for parameter optimization. The harmony search algorithm is used to optimize the parameters of the wavelet neural network, and the obtained optimal solution is used to optimize the initial value of the wavelet neural network model, and to predict the short-term traffic flow. And through the simulation experiment of the measured traffic flow data, it is verified that the prediction error of the HS-WNN in this paper is smaller than that of the WNN,HS-WNNhas a higher accuracy.
Design and implementation of remote experimental control platform
Authors: Wang Chenyang , Lin Zijian , Li Ruikai , Chen Chen 
Published: November 2020

Abstract
Based on the Internet of Things technology, our team has developed a remote wireless control experimental device based on the Internet of Things, which combines traditional experiments with Internet of Things technology. In the example experiment in this paper, the rotation angle of the corresponding motor on the experimental device is changed by means of buttons in the intelligent terminal APP. At the same time, the physical clamping and pushing control function of the control hub is exerted by mechanical push rod, bayonet and other workpieces, an d then the pushing force and rotating force are provided by the motor for the push rod. Finally, the camera is used to monitor the instrument panel and transmit the image data information via the wireless communication module to achieve remote control.
The improved equilibrium optimization algorithm with multiple updating discipline
Authors: Gao Zheng-Ming , Zhao Juan , Li Su-Ruo , Hu Yu-Rong 
Published: November 2020

Abstract
In this paper, a hybridization algorithm of the equilibrium optimization (EO) algorithm and the slime mould (SM) algorithm was proposed. The better performance of the SM algorithm in optimization both benchmark functions and real engineering problems were all encouraging. And consequently, the multiple updating discipline for individuals in swarms was introduced to the EO algorithm. Simulation experiments were carried out and the faster convergence, lower residual errors, higher accuracy verified the improved EO algorithm would perform better than the original one.
A Classification Method of Arrhythmia Based on Adaboost Algorithm
Authors: Zhang Bing , Wen Jingye , Ren Huihui 
Published: November 2020

Abstract
An arrhythmia classification model based on an adaptive boosting algorithm is proposed in this paper. According to the AAMI standard, 15 kinds of abnormal cardiac rhythms are grouped and the datasets are segmented by the non-crossover method. The electrocardiogram (ECG) signals are denoised by the filter method, and then divided into fixed-length ECG beats, and five features are extracted from time-domain and frequency-domain. Then, the base classifier of the algorithm and its optimal algorithm parameters is selected to realize the multi-classification of cardiac anomalies, aiming at mining hidden knowledge from human physiological data to detect human health status, making the diagnosis process more automatic, efficient, and intelligent.
Reducts in Intuitionistic Fuzzy β-covering ApproximationSpacesWhileRemovingandAdding Objects of theUniverse
Authors: Mao Lingling 
Published: November 2020

Abstract
The problem of reducts is the main problem in all rough set models. In the paper, we propose the concept of the reduct in an intuitionisticfuzzyβ-covering approximation space (IFCAS). Furthermore, reducts in IFCASs are investigated while adding and removing some objects of the universe. Firstly, the notion of the reduct in an IFCAS is presented. It can be regarded as the generalization of the reduct in covering and fuzzy β-covering approximation spaces. Then, two new IFCASs are presented while adding and removing some objects of the original universe. Finally,somepropertiesofreductsofintuitionisticfuzzy (IF)β-coveringsareinvestigatedwhileadding and removing someobjects.
Time series forecasting method based on frequent pattern mining
Authors: Qu Jintao , Cui Xiaohui , Meng Xiuyang , Zheng Senyang 
Published: November 2020

Abstract
Pattern Sequence-based Forecasting (PSF) is an effective method for time series prediction. However, the accuracy of this method depends on the selection of parameters such as the length of the pattern sequence and the number of clusters. In diverse time series data sets, these parameters are often priori unknown. This paper innovatively introduces a pattern mining method before the PSF pattern clustering to guide the clustering process and realize the automation of initial parameter selection. Experimental results show that the method proposed in this paper effectively eliminates the uncertainty of PSF caused by the selection of initial parameters. Compared with the original model, it improves the efficiency while ensuring the advantage of prediction accuracy.
Research on the Development Trend of Computer Science and Technology in the “Internet +" Era
Authors: Du Juan 
Published: November 2020

Abstract
In the process of the continuous development of social economy and science and technology, the demand for computer science and technology in various industries is constantly expanding, which to a large extent promotes the development of the computer industry. In the current process of social development, computer science and technology have changed people’s daily life and production methods to a large extent. Moreover, computer science and technology are closely related to information. Therefore, this article studies and analyzes the development trend of computer science and technology in the “Internet +" era from the perspective of social development to explore the practical application of computer science and technology. This will help further promote the development of computer science and technology in the “Internet +" era.
Application of Deep Learning in Vehicle Driverless Technology
Authors: chentian Ma 
Published: November 2020

Abstract
In recent years, due to the rapid development of deep learning, the application of deep learning in the field of unmanned vehicle driving has achieved good results through a large number of experiments. First of all,this paper introduces the development of driverless technology at home and abroad, then it introduces the theoretical basis of deep learning. The aim is to give readers a quick look at the history and current status of driverless technology and readers can understand the importance of deep learning in the field of driverless technology at the same time. Secondly, this paper introduced different intelligent scene recognition and compared them to find out which technology is more suitable for the current situation. Finally, the paper proposes the optimization scheme that can be improved or improved according to the shortcomings of the intelligent scene recognition technology and the problems and the development prospects of intelligent vehicles.
Discussion on the Ways to Improve the Financial Intelligence of Small and Micro Enterprises
Authors: Mu Ping 
Published: November 2020

Abstract
With the continuous development of information technology in my country, modern information technology has been widely and universally used in various industries. The development of corporate financial work has gradually applied information technology to it. Realizing financial intelligent management can effectively improve the level and effect of enterprise financial management. Because small and micro enterprises are generally relatively small in scale, insufficient funds, and low technical level. Therefore, in the process of promoting the construction and development of financial intelligence in the operation and development of small and micro enterprises, there are still problems such as insufficient professionalism of managers, weak development and use capabilities of intelligent financial software, and lack of complete systems and management systems. This has seriously affected the development and utility of financial intelligence. This article is mainly based on the related theories of financial intelligence, discussing and analyzing the status quo and problems of small and micro enterprises’ financial intelligence discovery. This article analyzes the reasons that influence the development of financial intelligence of small and micro enterprises and the ways to improve financial intelligence, hoping to help the management and development of small and micro enterprises.
Design of Bluetooth anti-lost Device Based on 51 Series Single Chip Microcomputer
Authors: Lu Xue , Sha Li , Luo Junbo 
Published: November 2020

Abstract
n order to solve the problems like the difficulty of people to retrieve the lost valuables in daily life and rampant theft in crowded areas, a practical Bluetooth anti-loss device based on 51 series single-chip microcomputer is proposed in this paper. It can effectively avoid the risk of users’ valuables being stolen or left behind, which has a very good market prospect. Based on the Bluetooth communication technology, this paper introduces the working principle of the Bluetooth tracker, and designs its hardware system circuit, including power module, crystal oscillator module, button module, alarm circuit, core controller, Bluetooth module and so on. The master and slave uses the same program design, by constantly sending handshake information to each other and using a timer to detect whether the other one is disconnected or not, achieves the anti-loss and anti-theft function. The Bluetooth anti-loss device designed has the advantages of high reliability, strong functionality, and high performance-to-price ratio.
Mask Guided Pedestrian Tracking from Single Point Initialization
Authors: Zhu Junan , Chen Tao , Cao Jingtai 
Published: November 2020

Abstract
Pedestrian tracking has a wide range of applications, such as intelligent monitoring and unmanned driving. In pedestrian tracking system, object detection algorithms are generally used to provide the initial bounding boxes for object tracking algorithms. If the bounding box provided by detection algorithm is not accurate, it will seriously affect the performance of object tracking. To solve this problem, this paper proposes a mask guided pedestrian tracking algorithm based on Siamese network. Firstly, Mask R-CNN is introduced to acquire exemplar image and its mask. Secondly, a light-weight convolutional neural network (CNN) is applied as the backbone of proposed algorithm. Thirdly, a channel attention module is introduced to our proposed algorithm and integrated with the light-weight CNN. The feature maps of the exemplar image and its mask are adjusted by a channel attention model and fused to enhance the discrimination ability of exemplar branch. Finally, our proposed tracker is trained GOT-10k dataset and evaluated on object tracking benchmark (OTB), experimental results show the excellent performance of proposed algorithm compared with state-of-the-art trackers.
Influence of equal-channel angular pressing on the functional characteristics of biodegradable Fe-based alloys
Authors: Rybalchenko O V , Anisimova N Yu , Kiselevsky M V , Rybalchenko G V , Martynenko N S , Tabachkova N Yu , Bochvar N R , Shchetinin I V , Tokar A A , Raab A G , Dobatkin S V 
Published: November 2020

AbstractIn this work samples of Fe-Mn alloys were subjected to equal-channel angular pressing (ECAP) in order to study the effect of the resulting microstructure on the mechanical properties, biodegradation rate, and biocompatibilityin vitroof the alloys. The microstructure of the alloys was studied by scanning and transmission electron microscopy, as well as by X-ray diffraction analysis. Mechanical properties were studied by microhardness and tensile tests. It is shown that as a result of deformation by the ECAP method, a predominantly austenitic ultrafine-grained (UFG) structure is formed, shear bands up to 600 nm thick and nanosized twins up to 40 nm thick were observed. The release of α-Mn particles in the ECAP process was revealed. Due to the structure refinement and twinning during ECAP, the strength characteristics of Fe-Mn alloys were significantly increased compared to the corresponding alloys in the initial annealed state. An increase in the propensity to biodegradation of UFG alloys with their satisfactory hemocompatibility was observed.
A St Petersburg Paradox for risky welfare aggregation
Authors: Goodsell Zachary 
Published: November 2020

Abstract
The principle of Anteriority says that prospects that are identical from the perspective of every possible person’s welfare are equally good overall. The principle enjoys prima facie plausibility, and has been employed for various theoretical purposes. Here it is shown using an analogue of the St Petersburg Paradox that Anteriority is inconsistent with central principles of axiology.
Influence of handler relationships and experience on health parameters, glucocorticoid responses and behaviour of semi-captive Asian elephants
Authors: Crawley J A H , Liehrmann O , Franco dos Santos D J , Brown J , Nyein U K , Aung H H , Htut W , Oo Z Min , Seltmann M W , Webb J L , Lahdenperä M , Lummaa V 
Published: November 2020

AbstractDeclining wild populations combined with accumulating captive populations of e.g. livestock, pets, draught and zoo animals have resulted in some threatened species with substantial proportions of their populations in captivity. The interactions animals have with humans in captivity depend on handler familiarity and relationship quality and can affect animal health, growth and reproduction with consequences for the success of conservation programmes. However, assessments of how specific human–animal relationships affect a range of physiological and behavioural outcomes are rare. Here, we studied semi-captive Asian elephants with detailed records of elephant–handler (mahout) relationships and veterinary management, allowing assessment of multiple welfare indicators in relation to specific mahout–elephant relationship lengths and mahout experience. These included measures of physiological stress (faecal glucocorticoid metabolite [FGM], heterophil:lymphocyte ratio [H:L]), muscle damage (creatine kinase [CK]), immunological health (total white blood cell count [TWBC]) and behaviour (response to mahout verbal commands). We found no evidence that FGM or H:L related to aspects of the mahout–elephant relationship. Longer overall mahout experience (i.e. years of being a mahout) was linked to increased muscle damage and inflammation, but the lengths of specific mahout–elephant relationships were inversely associated with muscle damage in working-age elephants. Elephants responded more to familiar mahouts in behavioural tasks and faster to mahouts they had known for longer. In summary, our results found little evidence that the mahout–elephant relationship affects physiological stress in this population based on FGM and H:L, but mahout experience and relationships were linked to other physiological responses (CK, TWBC), and elephants require behavioural adjustment periods following mahout changes.