bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effective Data Generation for E-banking Transactions Using Cycle-Consistent Adversarial Networks
Authors: Wang Xiaoguo , Zhao Han 
Published: July 2020

Abstract
In the anti-fraud research, the small amount of fraudulent transactions leads to extremely class imbalanced data. This problem becomes a bottleneck of fraud detection. In this paper, we apply the Cycle-Consistent Adversarial Networks (CycleGAN) to generate data for the minority class. Based on real e-banking transaction data, generators and discriminators are designed to generate synthetic data that meets the characteristics of e-banking transactions. Synthetic samples and real samples are mixed into the training of fraud detection model, and multiple metrics are used to verify the effect. Experimental results show that the synthetic data generated by CycleGAN can effectively improve the performance of the fraud detection model.
A Simplified Design of Automatic Energy Consumption Measuring Platform for Embedded Systems
Authors: Wu Huanjie , Chen Chun , Weng Kai 
Published: July 2020

Abstract
In this paper, a simplified design of automatic energy consumption measuring platform for embedded systems is proposed. A straightforward device named USB-TTL replaces the intermediate device in the original design and becomes the link between the host computer and the target board. The simplification makes the design of host computer software simpler and the whole platform more reliable. It also eliminates the need to design software for the intermediate device. In general, it has features similar to the original design. A series of test sets are also designed to verify its capabilities and accuracy. Compared to the original design, the simplified one has almost consistent accuracy, is easier to deploy, and requires less wiring and devices.
An Approach to Decrease Interference among Modalities in Emotion Detection
Authors: Dai Yu , Weng Jiancheng , Liu Yi , Liu Jian , Chang Boyu 
Published: July 2020

AbstractEmotion detection of video clips through multimodal information helps in a number of applications, including view mining, recommending system, public opinion and public sentiment monitoring. Current multimodal fusion techniques are applied to identify relevant information among modalities, which can introduce the interference of different modalities when detecting the emotion in the video. In this paper, we introduce a method which uses Q-Learning algorithm in attention-based network for decreasing interference among different emotion modalities. Experimental results prove that our method can improve the performance of basic attention-based network when detecting the emotion in the video.
A Quantitative Investment Model Based on Random Forest and Sentiment Analysis
Authors: Chen Mingqin , Zhang Zhenhua , Shen Jiawen , Deng Zhijian , He Jiaxing , Huang Shiting 
Published: July 2020

Abstract
In recent years, under the influence of economic globalization and anti-globalization, the stock market has experienced great fluctuations in China. Quantitative investment has attracted a lot of attention because of its characteristics of maintaining stable returns. Existing research is unilaterally based on quantitative data or qualitative data for analysis to construct a quantitative investment model. This paper considers both quantitative and qualitative data to construct a more comprehensive model than that in the past. Based on the optimized database, we present a combinational model named RF-SA, which is composed of random forest and sentiment analysis model. First of all, this paper uses the SBS algorithm to select the characteristics of stock transaction historical data, optimizes the prediction database, reduces data redundancy, and improves the accuracy of the model. Secondly, we analyze the characteristics of the Chinese stock market and study the advantages and disadvantages of many data mining algorithms, and select random forest model, the most suitable model, to build the first step of stock selection model. Then, through the analysis of public opinion, the confidence index of the stockholders is calculated; on this basis, the results of the RF model and the confidence index are combined to make a second choice for the stock, and the quantitative investment portfolio is obtained, and excess returns can be obtained. The results of empirical data show that, the RF-SA model obtains a higher rate of return than the investment model of the Shanghai Stock Index.
Towards End-to-End Face Recognition Method through Spatial Transformer
Authors: Wu Yanfang , Lu Xiaobo , Qin Chen 
Published: July 2020

Abstract
Face recognition technology is widely applied in daily life, but in most methods, similarity or affine transformation is employed to align face images according to five facial landmarks. The face alignment module is implemented independently, thus it’s difficult in end-to-end training. In this paper, the main purpose is to design a towards end-to-end trainable face recognition method based on indoor scenes. Due to that spatial transformer can implement any parametrizable transformation, we joint it with recognition network, making end-to-end training possible. Simultaneously, any prior knowledge on facial landmarks isn’t required. The model jointly with spatial transformer can achieve 0.3% higher accuracy than similarity transformation. Most downsampling methods ignore the sampling theorem, making convolutional networks not shift-invariant. We replace max-pooling by MaxBlurPool in spatial transformer network, and the accuracy is improved by 0.25%.
Design of Multifunctional Handheld Terminal for EOD Robot
Authors: Sun Tiancheng , Tan Yingzi 
Published: July 2020

Abstract
This paper designs a multifunctional handheld terminal for the explosive ordnance disposal robot (EOD robot), which can not only be used for one-to-one remote control of robots, but also be used as a remote monitoring platform for multiple robots. The hardware part of the terminal is based on the four-core processor Exynos4412, including power management, video decoding, data storage, network communication and other functional modules. The software part takes embedded Linux as the operating system platform, including human-computer interaction, network communication and data decoding modules. The system uses multithreading technology and draws the 3d model of the robot through OpenGL. The test results show that the terminal system is stable and reliable, and can meet the application requirements.
Research on Financial Aid Model of Colleges and Universities Based on Artificial Neural Network
Authors: Zhou Jun , Yang Mei , Wang Fang , Wang Chao 
Published: July 2020

Abstract
There are some problems in the recognition of financial aid objects in Colleges and Universities, such as being interfered by human factors and weak in quantification. The existing relevant research is mainly about policies, systems and measures, while the application of artificial intelligence in precise financial aid in colleges and universities needs further research. And the new generation of AI technology in deep learning can automatically extract data characteristics, and it can be used in the accurate identification of poor students, with the advantages of having no need for human intervention. This model designs and optimizes the precise identification model of university funding objects based on artificial intelligence technology, and achieves a satisfactory recognition rate, which explores a new technical way to improve the equity of education funding and its efficiency exploration.
A Method for Converting Inclusion Measure to Entropy of Interval Type-2 Fuzzy Sets
Authors: Zheng Gao , Wang Jing 
Published: July 2020

Abstract
In order to model imprecise information better, more and more scholars use type-2 fuzzy sets, among which interval type-2 fuzzy sets have practical application value, the reasons lie in that their secondary grades are all 1 and there are some fast algorithms for their operations. Inclusion measure and entropy are considered as two basilic parameters in fuzzy set theory because of their versatility, and those of interval type-2 fuzzy sets have become research hotspots nowadays. This paper mainly studies the relationship between the inclusion measure and entropy of interval type-2 fuzzy sets presented by Zheng et al., proposes and proves a transformation theorem that the former can be converted to the latter within the constraints of their axiomatic definitions. The result offers a reference for the theoretical research and practical application in the future.
The Improved Equilibrium Optimization Algorithm with Averaged Candidates
Authors: Gao Zhengming , Zhao Juan , Tian Xuejun 
Published: July 2020

Abstract
In this paper, we proposed the improvement of the newly raised equilibrium optimization (EO) algorithm by hybridizing the grey wolf optimization (GWO) algorithm. Simulation experiments were carried out and results showed that the hybrid EO algorithm with averaged candidates would perform better than the original one. Considering the better results and the smooth convergence curve on different types of benchmark functions, we recommend to withdraw the concept of equilibrium pool in the construction of the EO algorithm henceforth, and keep the guiding equation relevant to the averaged concentration of four best candidates instead.
Development of a Vision Guided Robot for Grafting Watermelon Based on Hole Insertion Method
Authors: Liu Kai , Jiang Kai , Mu Yanqiu 
Published: July 2020

Abstract
The grafting success rate of existing grafting robots will be significantly affected by individual differences in seedling’s shape. To circumvent this problem, a vision guided robot consisting of a Denso manipulator, a scion cutting unit, a rootstock holding unit, a Cognex machine vision system, a control system, and an end effector was developed. The robot autonomously performed its grafting task using a machine vision to locate the punching target point and the tip of scion hypocotyl, and then control system regulated the manipulator to punch a hole on the rootstock stem and accurately insert the watermelon scion into the hole. The function experiment showed that the punching angle of pin used by robot was 60° and the maximum inserting speed should not exceed 25 mm/s. Grafting experiment results showed that For the seedlings with individual differences in seedling’s shape, the success rate of present grafting robot(95.6%) is higher than that (83%) of a early grafting robot (2JC-600B). It is obvious that vision guidance reduce the negative effect of individual differences in seedling’s shape on grafting success rate.
Transmission Line Wire Following System Based on Unmanned Aerial Vehicle 3D Lidar
Authors: Zhang Ying , Liao Ruchao , Wang Yong , Liao Jiandong , Yuan Xinxing , Kang Taizhong 
Published: July 2020

Abstract
UAV(Unmanned aerial vehicle) wire checking is an efficient and scientific solution of transmission line operations. Aiming at the existing technology, this paper put forward a kind of based on 3D laser radar and ROS (Robot Operating System) of the UAV wire follow System. In the process of power transmission line inspection of wire, the system capture the wire by 3D laser radar mounted on the UAV and calculate the space distance between UAV and the wire and angle of this distance in 3D laser radar coordinate axis, control drone aircraft by PID(Proportion Integration Differentiation) algorithm in the attitude of UAV and inspection speed by the ROS on the onboard computer system platform for real-time wire following and automatic inspection task. Field experiments show that the system can effectively improve the efficiency and safety of wire inspection, and is conducive to the automation, safety and informatization of transmission line inspection process.
An Attention-Based LSTM Model for Stock Price Trend Prediction Using Limit Order Books
Authors: Li Yunhao , Li Liuliu , Zhao Xudong , Ma Tianyi , Zou Ying , Chen Ming 
Published: July 2020

Abstract
Stock price trend prediction has been a hot issue in the financial field, which has been paid much attention by both academia and industry. It is a challenging task due to the non-stationary and high volatility of the stock prices. Traditional methods for predicting stock price trends are mostly based on the historical OHLC (i.e., open, high, low, and close prices) data. However, it eliminates most of the trading information. To address this problem, in this paper, another type of stock price data, i.e., limit order books (LOBs), is used. For better exploring the relationship of the LOBs and stock price trend, inspired by the successful application of deep learning-based methods, an attention-based LSTM model is applied. The trend of stock price can be predicted by using the LOBs data of the previous day. By using the real stock price data of the China stock market, the effectiveness of the proposed model is validated by experimental results.
Study on the Positioning Scheme of Charging Pile Based on Ibeacon
Authors: Luo Jinman , Fen Youjun , Liu Piao , Ye Ruijing 
Published: July 2020

Abstract
With its advantages of low power consumption, anti-interference and low cost, ibeacon can not only provide users with positioning services, but also well adapt to the market. Therefore, this paper mainly studies and discusses the positioning scheme based on the ibeacon charging pile. According to the RSSI value, the distance between the bluetooth base station and the undetermined position node is derived, and the weighted triangulation algorithm is used to locate the undetermined position node. Finally, the a-star algorithm is used to quickly plan the shortest path.
Research on Ways to Improve College Students’ Sense of Acquiring Ideological and Political Courses under the Background of Artificial Intelligence
Authors: Duan Yuanpeng , Wu Shuting 
Published: July 2020

Abstract
Under the background of artificial intelligence, to promote the reform and innovation of college students’ ideological and political theory courses (hereafter this text will be abbreviated as “ideological and political courses”) and enhance their sense of acquisition of ideological and political courses. Survey and interview techniques were used to conduct a survey of “the current situation of college students’ ideological and political course acquisition”with nearly 300 college students as survey samples. College students’ perceived acquisition of ideological and political courses has some problems, such as unsatisfactory attendance, less active participation in ideological and political courses, and poor quality of homework after ideological and political courses. The hidden acquisition of ideological and political courses for college students has some issues that college students’ knowledge of the communist party of China is not deep enough, and their will to learn ideological and political courses is not firm enough. There are some main problems in college students’ awareness of ideological and political course practice, such as the small number of times they participate in the teaching practice of ideological and political theory course and the low degree of combining ideological and political theory with practical activities. Under the background of artificial intelligence, the way to improve college students’ acquisition of ideological and political courses is: The unique teaching technology and teaching resources of artificial intelligence are used to assist in the design of integrated ideological and political courses, the establishment of teaching information resources for ideological and political courses, and the optimization of the teaching process of ideological and political courses.
The Course Reform of the Modern Control Theory and Method Based on the Unmanned Aerial Vehicle
Authors: Lei Xusheng , Ma Jun 
Published: July 2020

Abstract
Focusing on the problems of the low efficiency and poor practical ability in the course of the modern control theory and method, the unmanned aerial vehicle is introduced in the class room teaching of the modern control theory and method. Using the engineering practice as the entry point, the unmanned aerial vehicle has been involved into the course system construction, head and tail teaching, homework, and examination process. Therefore, abstract theories and formulas are closely combined with concrete engineering practice. The learning interest and enthusiasm of elective students are motivated, and the ability to analyze and solve problems are improved. Five years of teaching practice results show that the reform of teaching methods has achieved good results.
Robust and Accelerated Frequency-Tuned Salient Object Detection via Color Quantization
Authors: Huang Zhe , Guo Baolong , Wang Geng , Li Cheng , Wei Zhifei 
Published: July 2020

Abstract
Frequency-tuned (FT) saliency detector has been widely used in various image processing and computer vision applications. However, removing high frequency noise and textures by a Difference of Gaussians (DoG) filter is still time-consuming, which hinders real-time execution of FT. In this paper, an improved algorithm is proposed to tackle the obstacles to performance improvement. It exploits color quantization within natural images and substitute Gaussian filtering process. Experimental results demonstrate that the proposed method runs up to about two times as fast as FT while resulting in almost the same saliency map.
Application Research of Virtual Reality Technology in Design
Authors: Fan Hongbin , Jiang Weisheng 
Published: July 2020

Abstract
With the improvement of people’s living standards, virtual reality technology has been applied to different industries, its own interactive feature, real-time feature and scene feature, which make it widely used in the field of architecture. This paper applies virtual reality technology to interior design, users can experience immersive-artistic conception in the virtual scene. We introduce the concept of virtual reality, and analyze the relationship between virtual reality technology and interior design; we study several main technologies of virtual reality, which include VRML modeling for installing interior virtual scene, using X3D technology for scene expansion of virtual interior design, Web technology is used to share virtual scenes. In the process of interior design, we put VRML technology into realizing the initialization of virtual scene, then adopt X3D technology to simulate the virtual scene, and proofread the generated virtual scene based on VRML technology, in order to realize online experience of the virtual scene, we display the effect of virtual interior design in the web environment, so that users can interact with the virtual interior design scene. By a large number of experiments, we prove that X3D technology can be used for displaying the virtual scene space in many dimensions, and the virtual environment has good maintainability; with the help of online-virtual reality technology, users can modify the scene of interior design, move the objects of scene, so that users can optimize the design of space according to their own wishes.
Allometric Growth Patterns of Fine Scale Fish Larvae and Its Ecological Significance
Authors: Yang Guiqiang , Wang Zhanquan , He Jie , Li Wentong , Yuan Ding 
Published: July 2020

Abstract
Ecological experiment was conducted to study the allometric growth of fine scale fish yolk-sac larvae and its significance in adaptation in early life stage. The results indicated organs such as feeding, breathing and swimming of larvae in the yolk sac stage are rapidly differentiated, and all key organs are allomorphic. In all parts of the body, the head length, tail fin length and body height are growing at a positive allometric speed, the trunk is growing at a slow speed; in the head organs, the rostrum length, eye diameter and head length are growing at a positive allometric speed; in the swimming organs, tail fin length is positive allometric growth; yolk sac length, yolk sac width and yolk sac height are positive allometric growth consumption. The fast development of feeding, breathing, swimming and other organs in yolk-sac larvae of fine scale fish, increases larval survival ability at the early stage in the shortest possible time, and there were important ecological significance to adapt the complex and changing external environment.
Research on NOx Emission Characteristics of Off-Road Diesel Machinery Based on Remote Monitoring Technology
Authors: Wang Jiguang , Bai Zhenyu , Xie Zhenkai , Zhang Xiaowen 
Published: July 2020

Abstract
In order to study and analyze the operating characteristics and NOx emission characteristics of typical non-road diesel machinery under actual operating conditions, this paper takes Excavators, Loader s and Forklifts operating at construction sites as objects, the On-board Emission Test Device (OETD in short) integrating Temperature Sensors, NOx sensors, GPS and GPRS is conducted to carry out experimental tests, and a Monitoring Platform Communicating with OETD by GPRS is uesd to collect the real-time data of the machinery’s geographical location, exhaust temperature and NOx concentration. The study result shows that the Excavator and Loader in the construction site are in long-term operating conditions and the average operating time is long; during the actual operating, the NOx emission concentration of the Loader is high and the range is large, mainly concentrated at 500 ∼ 900ppm, while the NOx of Excavators and Forklifts The emission concentration is relatively low, at 400 ∼ 450ppm.
Optimization of Coordination of Feeder Section and Connection of Operating Distribution Network
Authors: Liu Jun , Du Jian , Xu Chongyou , Lu Yiming , Li Yunshuo 
Published: July 2020

Abstract
The relation between section and connection of feeder of operating distribution network is researched. The method of an improved optimization algorithm is proposed to solve the problem of coordination of feeder section and connection under the operating constraint conditions. In the optimization process, in addition to the basic goals of load balance, number of the loads and total length of line segments in the feeder, other factors such as feeder specific structure, influence of tie switches and important customers are also considered. The optimal result is finally given as new locations of section switches and tie switches to realize the optimal operation of distribution network. The result is also used to guide the installation of distribution automation terminal devices and propose the self-healing strategy of distribution automation system.